272 results about "Maximum Pixel" patented technology

A method (and system) of eliminating visible artifacts in overlapped projections produced by a plurality of projectors, includes in areas outside of the overlap areas, raising an intensity of predetermined color pixels to match a level of the predetermined color in the overlap areas, and simultaneously with the raising of the intensity, scaling values of pixels in the overlap areas such that the values do not exceed the maximum pixel value of a single projector of the plurality of projectors.

A method of compressing an image data block is provided that includes computing a pixel residual for each pixel in the image data block except a non-residual pixel, computing a compression level for the image data block based on a minimum pixel residual value and a maximum pixel residual value of the pixel residuals, encoding a compression flag for the image data block, wherein the compression flag includes an indicator identifying the compression level and a first portion of bits from the non-residual pixel, and generating a compressed block comprising a second portion of bits from the non-residual pixel and the pixel residuals encoded using fixed length coding based on the compression level.

The present invention provides an apparatus and a method for image processing. The apparatus for image processing comprises an encoding circuit, which can select two reference pixels according to two reference pixels and produce a maximum pixel value and a minimum pixel value according the two reference pixels. The present invention further comprises a color-difference operational unit for selecting a plurality of color pixels as a basic pixel, a first color pixel, and a second color pixel. When encoding the basic pixel, a first color difference, and a second color difference, respectively, first encoding data corresponding to the basic pixel, second encoding data corresponding to the first color difference, and third encoding data corresponding to the second color difference are produced, respectively.

A parameterizable clip instruction for SIMD microprocessor architecture and method of performing a clip operating the same. A single instruction is provided with three input operands: a destination address, a source address and a controlling parameter. The controlling parameter includes a range type and a range specifier. The range type is a multi-bit integer in the operand that is used to index a table of range types. The range specifier plugs into the range type to define a range. The data input at the source address is clipped according to the controlling parameters. The instruction is particularly suited to video encoding/decoding applications where interpolations or other calculations, lies outside the maximum value and that final result will have to be clipped to saturation value, for example, the maximum pixel value. Signed and unsigned clipping ranges may be used that are not only powers of two.

The invention relates to a multi-focus image fusion method based on contrast pyramid transformation. Firstly preprocessing and image enhancement are performed on an input left focus source image and a right focus source image; then information entropy of the obtained enhanced images is solved and the weighted fusion coefficient is determined so that a primary fusion image is obtained; then contrast pyramid decomposition is performed on the two enhanced images and the primary fusion image so that decomposition layer sequence images are obtained; the weighted fusion coefficient is determined for the top layer image according to the pixel information difference between the images, and the fusion rule of taking the maximum pixel absolute value is performed on other layers of images; image reconstruction is performed on the obtained fusion image sequences so that the fusion image is obtained; and finally morphological gradient processing is performed on the fusion image and the two enhanced images, and secondary fusion is performed on the obtained images so that the final fusion result image is obtained. Fusion of the multi-focus images can be performed, and the fusion result image has the characteristics of being high in contrast, comprehensive and abundant in information, outstanding in edge and clear in details.

The invention provides an image processing method for automatically measuring the thickness of a fetal nuchal translucency from an ultrasonic image. The image processing method comprises the following steps that an ultrasonic instrument collects the input of an image and the importing of shooting parameters; quality analysis of an ultrasonic image to be detected of the fetal nuchal translucency based on Gabor feature matching is carried out; the ultrasonic image which accords with a measurement condition is screened according to a Gabor feature matching degree of the images in an image region and a training set; with regard to the ultrasonic image which accords with the measurement requirements, the position of the NT in the ultrasonic image is detected; a partial image of a clear NT line can be measured by a final output of the step through gradually-iterative threshold segmentation, canny operator edge detection and hough transform line detection; an NT target in the ultrasonic image can be measured; a K-MEANS method is used for classifying lines of NT target positions and upper and lower two clusters of line sections are aggregated to find out two measurement lines of the NT positions, and measuring a maximum pixel distance between the two lines; and the pixel distance of the NT is converted into a real length value according to a measuring scale of the shooting parameters.

An embodiment of the invention discloses a method and a device for compressing and decompressing reference frames. The method includes the steps of taking a 2x2 pixel block as a basic unit, and dividing a reference frame into a plurality of 2x2 pixel blocks; computing the difference between the maximum pixel and the minimum pixel value of pixel points included in each 2x2 pixel block; if the difference between the maximum pixel and the minimum pixel value of the pixel points included in each 2x2 pixel block is smaller than a first preset threshold value, expressing the difference between pixel value except the minimum pixel value of every pixel point included in the 2x2 pixel block and the minimum pixel value of the pixel point included in the 2x2 pixel block in a fixed bit digit mode less than 8 bits; packing the 2x2 pixel block into a data packet which is 32 bits in length, and sending the 32-bit data packet to a receiver. The method and the device for compressing and decompressing the reference frames are applicable to reference frame compression in the technical field of video compression.

A pixel correction system is provided. The pixel correction system includes a dynamic range detection system that receives test pixel data and adjacent pixel data and determines whether the test pixel data is within minimum pixel characteristic data and maximum pixel characteristic data of the adjacent pixel data. For example, if the pixel characteristic data is intensity, the dynamic range detection system detects bad pixels by identifying those pixels having an intensity value that is greater than the maximum intensity value of an adjacent pixel, or less than the minimum intensity value of an adjacent pixel. A dynamic range correction system coupled to the dynamic range detection system adjusts the test pixel data if the test pixel data is not within the maximum pixel characteristic data and the minimum pixel characteristic data, such as by setting the test pixel data equal to the maximum pixel characteristic data if the test pixel data is greater than the maximum pixel characteristic data, and by setting the test pixel data equal to the minimum pixel characteristic data if the test pixel data is less than the minimum pixel characteristic data.

A hand-supportable digital imaging-based bar code symbol reading system comprises: an automatic object presence detection subsystem; an image formation and detection subsystem having an area-type image sensing array with a field of view (FOV); a LED-based illumination subsystem having an LED illumination array for producing a field of narrow-band illumination within the FOV; an automatic light exposure measurement and illumination control subsystem; an image capturing and buffering subsystem; an image-processing bar code symbol reading subsystem; an input/output subsystem; and a system control subsystem for controlling the subsystems. The image-processing bar code symbol reading subsystem has a mode of image processing, wherein a captured digital image is automatically processed along a set of parallel virtual scan lines spaced-apart by a number of pixel-offset distances proportional to the maximum pixel height of the region of interest (ROI) in the captured digital image containing a bar code symbol.

The invention discloses a natural image matting method based on deep learning, and the method comprises the following steps: obtaining a matting data set, and carrying out the data enhancement; establishing a natural image matting model with an encoder-decoder structure; in order to reserve detail information, designing an encoder to enable the downsampling multiple to be 4, in order to compensatefor reduction of a receptive field caused by downsampling multiple reduction, introducing a cavity convolution to expand the receptive field, and storing the maximum pixel position in the maximum pooling operation so as to provide position information for an upsampling stage; in order to solve the multi-scale problem, a cavity space pyramid module is connected to the top of the encoder; designinga global context module in a decoder, wherein the global context module is used for fusing high-level features corresponding to the encoder and the decoder; finally training and testing. According tothe method, more detail information is reserved in the feature extraction process, and meanwhile, multi-scale features are associated, so that the model can capture global information, model processing details and large-area transparent objects are facilitated, and the matting quality is improved.

The invention discloses a no-reference color image quality assessment method on the basis of the sparse representation and belongs to the technical field of digital image processing. For images to be evaluated, the no-reference color image quality assessment method includes selecting an image block with the maximum pixel spatial correlation difference from an HSV (hue, saturation and value) color space, and matching elements in a dictionary by the image blocks, wherein each element in the dictionary is composed of the image block with the maximum pixel spatial correlation difference in a training image set, DMOS (differential mean opinion score) and the maximum difference; adopting a matching and tracking method to obtain sparse representation of the images to be evaluated in the dictionary, and setting up the color image quality assessment indexes by the DMOS and the maximum difference of the selected elements from the dictionary. The element dictionary forming method is simple and clear, the extracted characteristics more conform to visual perception of human eyes, the integral algorithm is simpler, and the quality assessment results are more accurate.

A system is disclosed for equalizing the distribution of pixel intensities in an image displayed by an oscilloscope. In a primarily software implementation, the maximum pixel intensity (I) present in the rasterized input image, the maximum available display intensity (P) and the desired image resolution (R) are the input variables which permit the calculation of thresholds or bins to which each pixel is assigned. By iteratively performing the analysis of existing pixel intensities and bin thresholds, the number of pixels in each bin may be optimized to form an equalized histogram. Another implementation of the histogram equalization system utilizes software to optimize a hardware-based histogram collector.

The invention discloses a robot autonomous positioning method and device based on a depth camera. Different from a general visual positioning scheme in which a color image or a gray image is used forextracting a feature, a depth image with depth information is converted into a gray image containing the depth information, a unit pixel is equal to a fixed depth value during converting, and then linear converting is performed; or the depth value is divided by the maximum depth in the scene, and then multiplied by a maximum pixel value; feature points are extracted from the converted gray image containing the depth information and then mapped to a three-dimensional world through the depth value of the corresponding pixel, the obtained feature points are matched with reconstructed map points,and the current accurate position and orientation of a mobile robot are calculated. The disadvantage that a traditional visual positioning method is too sensitive to the change of ambient light changeis overcome, and high universality is achieved.

The invention relates to a reversible data hiding method. The reversible data hiding method comprises: a step of pre-processing: partitioning an original pixel-domain image, and sorting according to a gray value in a block; a step of identifying: detecting and identifying a sorted sequence, and identifying a characteristic block; a step of embedding watermark information: embedding the watermark information in the characteristic block through a second embedding method; and a step of embedding auxiliary information: embedding corresponding auxiliary information. According to the invention, embedding of the watermark information according to requirements is realized; the equivalent maximum pixel redundancy in the image can be sufficiently mined; multi-bit embedding at one position is realized; the information capacity is effectively increased; and simultaneously, seamless fusion of a first embedding method and the second embedding method is effectively realized.