36results about How to "Avoid Noise Amplification" patented technology

A method for processing a sparsely populated color digital image having colored pixels to produce a fully populated and noise clean color image including noise cleaning the sparsely populated image using a variable noise cleaning kernel to provide a noise clean sparsely populated color digital image; and interpolating the noise clean sparsely populated image for producing color pixels with appropriate values missing from the sparsely populated color digital image by interpolating the color values for missing pixels from neighboring color pixels.

Image compression, decompression and motion detection methods are described. Two temporally adjacent frame images, a previous time frame and a current time frame, are compressed in round-off and averaging techniques. Next, according to the compressed data of two corresponding pixels of the two frame images, whether or not the pixel of the current time frame image is of a motion picture is detected. If the pixel is of a motion picture, the compressed pixel data of the previous time frame image is decompressed, and an overdrive process is performed on the decompressed pixel data and the original pixel data of the current time frame image to produce an overdrive output. If the pixel is not of a motion picture, an overdrive process is not performed.

The invention belongs to the technical field of image exposure, and relates to an automatic exposure control method. The automatic exposure control method comprises the steps of S1, carrying out imagecollected by using binocular vision and an active structural light source projection method, and obtaining the last image collected each time; S2, obtaining the average brightness of the image by using a dynamic partitioning and dynamic weight coefficient adjusting method; S3, judging whether the average brightness of the image is within a target brightness range or not, if so, not carrying out exposure compensation and terminating the automatic exposure control, otherwise, entering the step S4; and S4, obtaining the difference between the average brightness of the image and the target brightness, selecting the corresponding step size for exposure compensation according to the difference and returning back to the step S1. The automatic exposure control method soles the problems of great noise signal, insufficient or excessive exposure of a target area due to excessive contrast between the target object and the background, excessively long adjustment time and excessively great difference between the image brightness and the target brightness in the prior art.

A small detail restoration (SDR) system implements an SDR method for processing digital images, especially in DTV applications prior to image resampling process in a scaler unit. The SDR system performs three image processing functions: detail extraction, smoothness checking, and small detail detection on an input image. The results of the three processing functions are combined, amplified and added back to original image to obtain the final resulting output image. The SDR method is applied in the texture or small detail area of image while the strong edge area is not enhanced. For example, in DTV applications, the SDR method is suitable for enhancing the digital image prior to image resampling process in the scaler unit.

The invention discloses a speech signal self-adaptive adjusting method, a speech signal self-adaptive adjusting device, a mobile terminal and a storage medium. The speech signal self-adaptive adjusting method comprises the steps of acquiring a speech signal in an environment in real time when the mobile terminal is in a hands-free calling mode, acquiring a distance between the mobile terminal and a caller in real time, analyzing the speech signal, acquiring vocal print features of sounds from different sources in the speech signal, identifying a target vocal print feature belonging to the caller, determining a speech amplitude value of the sound to which the target vocal print feature belongs in the speech signal, and adjusting a loudness degree and a frequency degree of the sound to which the target vocal print feature belongs according to the speech amplitude value and the distance. Through identifying the target vocal print feature of the caller in the speech signal, the sound of the caller can be adjusted according to the speech amplitude value of the sound to which the target vocal print feature belongs and the distance between the mobile terminal and the caller, thereby being capable of effectively avoiding the problem of amplifying environment noise, improving calling quality and improving use experience.

An embodiment of the invention provides a self-adaptive adjustment method and device for earphone calls, a mobile terminal and a storage medium. The method comprises the steps as follows: when the mobile terminal is in an earphone call mode, a voice signal in the environment is acquired and analyzed, a target voiceprint feature is obtained through matching from analyzed voiceprint features by the aid of a preset voiceprint feature recognition library, the voice amplitude of the voice with the target voiceprint feature in the voice signal is determined, and the loudness value and the frequency value of the voice with the target voiceprint feature in the voice signal are adjusted according to the voice amplitude. Compared with an AGC (automatic gain control) self-adaptive gain adjustment method, the self-adaptive adjustment method has the advantages that the problem of ambient noise amplification can be solved effectively and the call quality can be improved while the call volume is increased.

A composite video signal has a chrominance signal (14) and a luminance signal (10). A method and apparatus are disclosed for adjusting the chrominance signal (14) to obtain an enhanced chrominance signal (15) in which at least some transitions in the enhanced chrominance signal (15) align more closely with edges in the luminance signal (10) than transitions in the original chrominance signal (14) align with edges in the luminance signal (10). An edge in the luminance signal (10) of the composite video signal is detected (11). The position of the edge relative to a current pixel is detected (11). The chrominance of the current pixel is adjusted (13) in accordance with at least the position of said current pixel relative to the edge to obtain an enhanced chrominance signal (15).

This invention relates to image contrast intensifying method, comprising the following steps: first, scanning a piece of image to sequentially calculate brightness variance of two adjacent pixels; then, comparing the variance to pre-setting threshold value, if large, generating a positive force sequence, if smaller, generating a negative force sequence; third, repeatedly operating the generation and accumulating calculation of the positive and negative ones to get a net positive force sequence and a net negative one until judging termination; fourth, forming a net force sequence by net positive one minus added-weight factor net negative one, and integrating and normalizing it to get a spreading force function; fifth, linear combining the spreading force function and original brightness switching function to get a new switching function for adjusting original brightness to intensify image contrast.

Image compression, decompression and motion detection methods are described. Two temporally adjacent frame images, a previous time frame and a current time frame, are compressed in round-off and averaging techniques. Next, according to the compressed data of two corresponding pixels of the two frame images, whether or not the pixel of the current time frame image is of a motion picture is detected. If the pixel is of a motion picture, the compressed pixel data of the previous time frame image is decompressed, and an overdrive process is performed on the decompressed pixel data and the original pixel data of the current time frame image to produce an overdrive output. If the pixel is not of a motion picture, an overdrive process is not performed.

The invention discloses a sample balancing method in data mining, which randomly divides the samples in most classes into equal frequency according to the proportion of positive and negative samples.The classification algorithm model is constructed by combining each group of most class samples with the total number of sparse class samples. Finally, the model integration method is used to fuse multiple models. The invention integrates the advantages of two methods of over-sampling and under-sampling, and improves the generalization ability of the model.

The invention discloses a super-resolution processing method for an augmented Lagrangian real-beam radar angle. Firstly a linear FM signal is transmitted in real-beam scanning, thereby obtaining a two-dimensional echo signal in a radar irradiation area. Then distance-direction high resolution is realized through distance-direction matched filtering. Then a signal model of an azimuth echo is constructed according to a scanning imaging process of a radar antenna. Then according to a principle of minimizing noise power influence, a deconvolution problem is converted to a constraint optimization problem. Furthermore solving of an objective function is realized by means of an augmented Lagrangian method, and an objective scattering coefficient is obtained through iterative inversion, thereby realizing super-resolution for the azimuth of a scanning radar. The super-resolution processing method settles a problem of low azimuth resolution in a real-beam scanning radar imaging mode.

Image compression, decompression and motion detection methods are described. Two temporally adjacent frame images, a previous time frame and a current time frame, are compressed in round-off and averaging techniques. Next, according to the compressed data of two corresponding pixels of the two frame images, whether or not the pixel of the current time frame image is of a motion picture is detected. If the pixel is of a motion picture, the compressed pixel data of the previous time frame image is decompressed, and an overdrive process is performed on the decompressed pixel data and the original pixel data of the current time frame image to produce an overdrive output. If the pixel is not of a motion picture, an overdrive process is not performed.

The invention relates to a regional new energy power supply structure optimization prediction method and system, and a "total amount-structure-component" three-phase comprehensive optimization prediction model is established. The method includes: predicting a new energy power supply on-grid electric quantity total amount by employing an improved grey prediction model, optimizing a prediction result of the power supply on-grid electric quantity total amount, and obtaining a prediction result X of the new energy power supply on-grid electric quantity total amount; predicting a new energy on-gridelectric quantity structure by employing a dynamic planning prediction model based on error optimization, and obtaining a structure prediction result F of the new energy power supply branch power supply type; and obtaining a component prediction result R of the new energy power supply branch power supply type by employing the obtained prediction result X of the new energy power supply on-grid electric quantity total amount and the structure prediction result F of the new energy power supply branch power supply type. According to the method and system, optimized prediction of a regional new energy power supply structure can be realized, the application range is wide, and the prediction precision is high.

The invention belongs to the technical field of image exposure, and relates to a projection method based on automatic exposure control and an automatic switching projection pattern. The method comprises the following steps: S1: performing image collection and performing three-dimensional imaging; S2: acquiring the last image of each collection, and acquiring average brightness of the image; S3: judging whether the average brightness of the image is within a target brightness range; S4: acquiring a difference value between the average brightness of the image and the target brightness, and performing exposure compensation; S5: performing three-dimensional imaging quality evaluation; S6: judging whether a coding pattern is switched; and S7: selecting a group of patterns with the highest evaluation of three-dimensional imaging quality for projection. By adoption of the projection method disclosed by the invention, the following problems in the prior art are solved: the noise signal is large, it is difficult to maintain stable high-quality imaging, when the contrast between a target object and the background is too large, a target area is underexposed or overexposed, the adjustment timeis too long, and the difference value between the image brightness and the target brightness is too large.

The invention belongs to the technical field of automatic control, and particularly relates to an integral separated PID control method, which comprises a tracking differentiator TD1 for arranging a transition process of an input error, a PID controller using an integral separation algorithm and a feedback loop filter TD2, wherein an error tracking signal and an error differential signal of the input error signal are obtained through the tracking differentiator TD1; the integral link adopts a new integral separation algorithm, which can reasonably change the integral gain coefficient accordingto the error and the separation threshold value; the integral link constitutes an integral separated PID controller together with a proportional link and a differential link; the integral separated PID controller outputs a controlled quantity signal acting on a controlled object; the tracking differentiator TD2 is added to the feedback loop as a feedback loop filter for filtering the measurementnoise of the output signal. The integral separated PID control method in the invention can improve the response speed of the control system, reduce the overshoot amount, and reduce the adverse effectsof integral feedback.

A restoration filter generation device which generates a restoration filter for performing a restoration process on luminance system image data, the restoration process being based on a point-image distribution in an optical system, the luminance system image data being image data relevant to luminance and being generated based on image data for each color of multiple colors, the restoration filter generation device including an MTF acquisition device which acquires a modulation transfer function MTF for the optical system; and a restoration filter generation device which generates the restoration filter based on the modulation transfer function MTF, the restoration filter suppressing an MTF value of image data for each color of the multiple colors to 1.0 or less at least in a region of a particular spatial frequency or less, the image data for each color of the multiple colors corresponding to the luminance system image data after the restoration process.

The invention provides a deep abnormal body boundary recognition and step-by-step enhancement method and system, a medium and equipment. According to magnetic field three-component data and magnetic gradient tensor data of an object to be recognized, reverse tangent operation is performed to obtain a preliminary recognition result of a deep abnormal body boundary; by utilizing magnetic gradient tensor data components and a boundary recognition method improved by the reverse tangent operation, the deformation of the deep abnormal body boundary is inhibited; and by utilizing an idea of gamma conversion in image processing, parameter adjustable image enhancement is performed according to enhancement shadow area contrast or high-brightness area contrast of different value selectivity, a targetbody boundary is further highlighted, and a final recognition result is obtained.

The invention relates to an image enhancement method based on controlled diffusion. Firstly, Gamma transform is applied to enhance the fundus image to a proper gray level. Secondly, the self-similarity filter is used to denoise the transformed image, especially the region of interest which needs to be extracted from the image. Finally, the proposed controllable diffusion equation method is used tofurther sharpen the image, so that the artifacts caused by over-enhancement can be avoided while the important details are highlighted.

The invention discloses a simulation optimization method for a motor simulator, belongs to the technical field of power simulation in the technical field of power electronics, and aims to solve the technical problem of low test precision of a method in the prior art. The method comprises the following steps that: S101, a first inductor is connected with a second inductor in series, and the precision of the second inductor is higher than that of the first inductor; S102, a second change rate is determined, wherein the second change rate is determined by collecting the voltage of the second inductor and is sent to a controller; S103, determining a first change rate, wherein the first change rate is determined by collecting a current value of the simulation motor simulator which is only coupled with the first inductor; and S104, filtering processing is performed on the first change rate and the second change rate to determine a third change rate, and the third change rate is outputted through the controller. The simulation function of the motor simulator is improved, and the requirement for high precision of the simulation structure of the motor simulator is met.

The invention discloses a mixed regularization azimuth super-resolution imaging method, which is applied in the field of radar imaging and aims at traditional L 2 Regularized imaging method has low resolution, traditional L 1 For the problem of poor anti-noise performance of the regularized imaging method, the present invention first establishes a convolution-like model of scanning radar azimuth echo; then, through L 2 The regularization method preprocesses the echo signal; finally, based on the preprocessing result, L 1 The norm characterizes the target sparse prior information to reconstruct the target function, and the method of iteratively reweighting the norm is used to solve the target function. The innovation of the present invention lies in: combining L 1 Regular term and L 2 The advantages of the regular term, use L 2 The norm weakens the influence of noise and avoids the noise being amplified in the iterative process, and then uses L 1 The sparse nature of the norm improves the azimuth resolution of imaging. This method is different from the conventional L 2 Compared with the regularization method, the azimuth resolution is improved, and compared with the traditional L 1 Compared with the regularization method, the noise is well suppressed.

The invention provides an energy efficient distributed relay option algorithm in a wireless cooperative relay network. The relay network comprises a source node, a target node and a plurality of relay nodes. A method for selecting relay nodes comprises the following steps of: respectively determining the channel states and the energy states of all relay nodes at any time slot according to channel state models and energy state models of the plurality of relay nodes; calculating the system rewards of each relay node through a preset system reward model on the basis of the channel states and the energy states; and selecting a relay node for each time slot, wherein the selected relay nodes ensure that the obtained system reward in the whole data transmission process is maximized.

The invention discloses a power grid side harmonic current suppression method for a non-electrolytic capacitor compressor controller, and belongs to the field of variable frequency air conditioner driving. According to the method, a power grid side voltage and a direct-current bus voltage serve as input quantities, a differential component of a power grid current is indirectly obtained, and a current compensation quantity is obtained through a feed-forward compensation module to compensate a q-axis current of a compressor. The feed-forward compensation module comprises a discretization unit, a linear adjustment unit and an amplitude limiting unit. Aiming at the large fluctuation change of the q-axis current reference value after the compensation is applied, an anti-saturation integral estimation regulator is adopted to effectively control the q-axis current, so that the power grid side input current is indirectly controlled. The method provided by the invention does not need to additionally collect power grid current, is easy to engineering realization, and can effectively improve power grid current distortion and suppress high-frequency harmonic current, so that the current meets the harmonic standard.

The invention discloses a seismic data attenuation compensation method in a synchronous extrusion transform domain. In the synchronous extrusion transform domain, the attenuation compensation process is represented as an inverse problem with L1 norm regularization, solving is carried out through an iterative re-weighting algorithm, and thus, stabilized attenuation compensation is realized. Synchronous extrusion transform can suppress diffusion of time frequency energy, a more sparse and highly-localized time frequency representation is obtained, and thus, attenuation compensation on nonstationary seismic signals is facilitated. The method uses the sparse properties of signals in the synchronous extrusion transform domain, the L1 norm regularization method is introduced to stabilize the attenuation compensation process, and a noise amplification problem is thus avoided. The disclosed method is used to realize compensation on seismic attenuation effects, the seismic data resolution can be enhanced, and convenience is brought to subsequent seismic inversion and reservoir description.

The invention discloses an image enhancement method and system based on image decomposition and spectrum transformation, and relates to the technical field of image processing, and the method comprises the steps: carrying out the path separation of an original image, and dividing the original image into a noise layer image and a basic layer image; performing detail extraction on the base layer image, and dividing the base layer image into a structure layer image and a detail layer image; carrying out truncated adaptive brightness stretching on the structure layer image; performing highlight removal processing and detail color processing on the detail layer image; performing detail enhancement on the detail layer image after the detail color processing; performing weighted fusion on the detail layer image after detail enhancement and the truncated structure layer image after adaptive brightness stretching to obtain a processed base layer image; and performing equal-proportion fusion on the processed base layer image and the noise layer image, and outputting a result image. The method is particularly suitable for endoscopic images in medicine, details in the endoscopic images can be amplified in a self-adaptive mode, noise influences are eliminated, and the problem that local modules are too bright or too dark is solved.

The invention relates to a regional new energy power supply structure optimization prediction method and system, and a "total amount-structure-component" three-phase comprehensive optimization prediction model is established. The method includes: predicting a new energy power supply on-grid electric quantity total amount by employing an improved grey prediction model, optimizing a prediction result of the power supply on-grid electric quantity total amount, and obtaining a prediction result X of the new energy power supply on-grid electric quantity total amount; predicting a new energy on-gridelectric quantity structure by employing a dynamic planning prediction model based on error optimization, and obtaining a structure prediction result F of the new energy power supply branch power supply type; and obtaining a component prediction result R of the new energy power supply branch power supply type by employing the obtained prediction result X of the new energy power supply on-grid electric quantity total amount and the structure prediction result F of the new energy power supply branch power supply type. According to the method and system, optimized prediction of a regional new energy power supply structure can be realized, the application range is wide, and the prediction precision is high.

The invention discloses an augmented Lagrangian real-beam radar angle super-resolution processing method. Firstly, a linear frequency modulation signal is transmitted while the real beam is scanning to obtain a two-dimensional echo signal of the radar irradiation area, and then the range-direction matching filter is used. Realize high resolution in the range direction, then construct the signal model of the azimuth echo according to the process of radar antenna scanning and imaging, and then convert the deconvolution problem into a constrained optimization problem according to the minimum noise power influence criterion, and use the augmented Lagrangian The method realizes the solution of the objective function, and iteratively inverts the scattering coefficient of the target to achieve the purpose of azimuth super-resolution of the scanning radar. The invention preferably solves the problem of low azimuth angle resolution in the real beam scanning radar imaging mode.