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2045 results about "Image restoration" patented technology

Image Restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blur, noise and camera mis-focus. Image restoration is performed by reversing the process that blurred the image and such is performed by imaging a point source and use the point source image, which is called the Point Spread Function (PSF) to restore the image information lost to the blurring process.

Method of digital image enhancement and sharpening

InactiveUS6879735B1MinimizesImage enhancementImage analysisRadiographic Image EnhancementPresent method
A method of digital image enhancement and sharpening (11, 12) which may be applied to restoration of blurred digital images of arbitrary origin. The method uses a specially formulated constraint (15) to reconstruct the original images. In particular, the constraint of the present method minimizes the area where strong image parameter variations and discontinuities occur. This new constraint is called a minimum gradient support (MGS) constraint. The MGS constraint generates a stable sharp solution of the linear ill-posed image restoration equation with an arbitrary blurring operator.
Owner:UNIV OF UTAH RES FOUND

Compressed low-resolution image restoration method based on combined deep network

The present invention provides a compressed low-resolution image restoration method based on a combined deep network, belonging to the digital image / video signal processing field. The compressed low-resolution image restoration method based on the combined deep network starts from the aspect of the coprocessing of the compression artifact and downsampling factors to complete the restoration of a degraded image with the random combination of the compression artifact and the low resolution; the network provided by the invention comprises 28 convolution layers to establish a leptosomatic network structure, according to the idea of transfer learning, a model trained in advance employs a fine tuning mode to complete the training convergence of a greatly deep network so as to solve the problems of vanishing gradients and gradient explosion; the compressed low-resolution image restoration method completes the setting of the network model parameters through feature visualization, and the relation of the end-to-end learning degeneration feature and the ideal features omits the preprocessing and postprocessing; and finally, three important fusions are completed, namely the fusion of the feature figures with the same size, the fusion of residual images and the fusion of the high-frequency information and the high-frequency initial estimation figure, and the compressed low-resolution image restoration method can solve the super-resolution restoration problem of the low-resolution image with the compression artifact.
Owner:BEIJING UNIV OF TECH

Method and device for identifying reticulate pattern face image based on multi-task convolutional neural network

The present invention discloses a method and a device for identifying a reticulate pattern face image based on a multi-task convolutional neural network. The method comprises the steps of: collecting reticulate pattern face image and corresponding clear face image pairs, then using the multi-task convolutional neural network to respectively design object functions based on regression and classification, training a face image reticulate pattern removing model, and finally inputting the reticulate pattern face image into the trained reticulate pattern removing model to obtain a face image without reticulate pattern, thereby performing subsequent face image identification tasks. According to the method, a multi-task learning frame is adopted, the task for restoring a reticulate pattern image to a clear image is expressed as two object functions which are assistant with each other, and the convolutional neural network is utilized to learn complicated nonlinear transformation referred therein. The method not only effectively improves convergence rate during model training, but also can greatly improve image restoration effect and generalization ability, thereby greatly improving identification accuracy rate of the reticulate pattern face image.
Owner:INST OF AUTOMATION CHINESE ACAD OF SCI

Image compression method, image restoration method, program and apparatus

An image compression divides an input image into blocks having the predetermined number of horizontal and longitudinal pixels, and scans the divided blocks in a main scan direction and a sub scan direction so as to select them in order as a processing block, and selects as a reference block a block in which positional relation with the selected block and a relation of a pixel value satisfies a predetermined condition. Subsequently, the pixel values of the processing block and the reference block are subjected to an exclusive-OR (XOR) so as to generate a differential image, and in case the differential image satisfies the predetermined condition, the processing block is replaced with the differential image. Further, the image including the differential image obtained by executing the block replacement in the processing block is encoded, and the code data obtained by executing this image encoding, the presence or absence of replacement with the differential image of each processing block obtained by executing the block replacement, and positional information of the reference block are combined and outputted. The image decoding is executed in such way that the image including the differential image from the code data is decoded, and this decoded image is decoded into the original image by an exclusive-OR with the processing block which is divided into blocks and the reference block.
Owner:FUJITSU LTD

Significant object detection method based on sparse subspace clustering and low-order expression

ActiveCN105574534ASolve the problem that it is difficult to detect large-scale salient objectsOvercome the difficulty of detecting large-scale saliency objects completely and consistentlyImage enhancementImage analysisGoal recognitionImage compression
The invention discloses a significant object detection method based on sparse subspace clustering and low-order expression. The method comprises the steps of: 1, carrying out super pixel segmentation and clustering on an input image; 2, extracting the color, texture and edge characteristics of each super pixel in clusters, and constructing cluster characteristic matrixes; 3, ranking all super pixel characteristics according to the magnitude of color contrast, and constructing a dictionary; according to the dictionary, constructing a combined low-order expression model, solving the model and decomposing the characteristic matrixes of the clusters so as to obtain low-order expression coefficients, and calculating significant factors of the clusters; and 5, mapping the significant value of each cluster into the input image according the spatial position, and obtaining a significant map of the input image. According to the invention, the significant objects relatively large in size in the image can be completely and consistently detected, the noise in a background is inhibited, and the robustness of significant object detection of the image with the complex background is improved. The significant object detection method is applicable to image segmentation, object identification, image restoration and self-adaptive image compression.
Owner:XIDIAN UNIV

Efficient method to predict integrated circuit temperature and power maps

The temperature distribution associated with a design of an integrated circuit is calculated by convoluting a surface power usage represented by a power matrix with a heat spreading function. The heat spreading function may be calculated from a simulation of a point source on the integrated circuit using a finite element analysis model of the integrated circuit or other techniques. To account for spatial variations on the chip, the heat spreading function may be made dependent on position using a position scaling function. Steady-state or transient temperature distributions may be computed by using a steady-state or transient heat spreading function. A single heat spreading function may be convolved with various alternative power maps to efficiently calculate temperature distributions for different designs. In an inverse problem, one can calculate the power map from an empirically measured temperature distribution and a heat spreading function using various de-convolution techniques. While the forward problem is analogous to image blurring, the inverse problem is analogous to image restoration.
Owner:UNIV OF CALIFORNIA SANTA CRUZ

Image processing method and image processing apparatus for image restoration

The image processing method includes a step of acquiring an input image produced by image capturing using an optical system, an image restoration step of performing an image restoration process on the input image to produce a restored image, the image restoration process using an image restoration filter produced based on an optical transfer function of the optical system, and a color shift detection step of detecting color shift included in the restored image, the color shift corresponding to chromatic aberration of magnification of the optical system. The method further includes a restored image color shift reduction step of performing a color shift reduction process on the restored image to reduce the color shift detected in the color shift detection step.
Owner:CANON KK

Video image super-resolution reconstruction method

The invention relates to a video image super-resolution reconstruction method. The method comprises the steps that 1), for a plurality of low-resolution images capable of being obtained through the same scene, continuous sequence frames of needed videos are selected and converted to static JPG or BMP files, and continuous multi-frame sub pixel images in a pixel are selected with the combination of scene parameters; 2) according to the image sequence frames of the multi-frame sub pixel images, a target interest point is selected, and motion estimation of a block-shaped target is conducted; 3) according to a motion estimation result, a non-uniform interpolation reconstruction algorithm is adopted, and a high-resolution image is reconstructed. According to the video image super-resolution reconstruction method, the resolution, on details, of a video image can be improved on the premise that the image quality of an existing imaging device is not improved, the defects in methods for traditional image restoration, enhancement and the like are overcome, and the video image super-resolution reconstruction method has the advantages of being easy and convenient to operate, and high in efficiency. The video image super-resolution reconstruction method can supply optimized image data foundations to the application in the image data field, and therefore the city video information application field can be enlarged.
Owner:BAINIAN JINHAI SCI & TECH

Remote sensing image fusion method based on sparse representation

The invention discloses a remote sensing image fusion method based on sparse representation. The method comprises the following steps of: firstly, establishing a linear regression model between a multispectral image and a brightness component thereof; secondly, performing sparse representation on a panchromatic image and the multispectral image by using high and low resolution dictionaries respectively, and acquiring sparse representation coefficients of the brightness component of the multispectral image according to the linear regression model; thirdly, extracting detail components according to the sparse representation coefficients of the panchromatic image and the brightness component, and implanting the detail components to the sparse representation coefficients of each band of the multispectral image under a general component replacement fusion framework; and finally, performing image restoration to obtain a multispectral image with high spatial resolution. According to the method, the sparse representation technology is introduced into the field of remote sensing image fusion, so that the defect that high spatial resolution and spectral information cannot be simultaneously preserved in the prior art is overcome; and the fusion result of the method is superior to that of the conventional remote sensing image fusion method on the aspects of spectral preservation and spatial resolution improvement.
Owner:SHANGHAI JIAO TONG UNIV

Image enhancement in the mosaic domain

Imaging apparatus includes a mosaic image sensor (24), which is configured to generate a stream of input pixel values belonging to a plurality of input sub-images, each sub-image responsive to light of a different, respective color that is incident on the mosaic image sensor. An image restoration circuit (26) is coupled to receive and digitally filter the input pixel values in each of the input sub-images so as to generate a corresponding plurality of enhanced output sub-images. An image signal processor (ISP) (28) is coupled to receive and combine the plurality of the output sub-images in order to generate a color video output image.
Owner:DIGITALOPTICS CORPORATION

Laser two-dimension code identification method based on image restoration

The invention discloses a laser two-dimension code identification method based on image restoration and belongs to the technical field of image processing. The laser two-dimension code identification method includes steps of preprocessing acquired metal part laser two-dimension code images, acquiring outer contour of two-dimension codes by means of image morphology, detecting outer edges of the two-dimension codes by Soble operator, roughly and accurately positioning the two-dimension codes, partitioning the two-dimension code images, restoring and identifying and the like. By the laser two-dimension code identification method, the more satisfying two-dimension code images can be redrawn, the two-dimension code images can be restored and identified, the problem that an existing identifying method is hard to extract correct two-dimension code data due to the fact that laser two-dimension code images on metal pieces are always fuzzy or defective because of chemical reaction of many metal products during marking and illumination and oil contamination and the like during acquisition is solved, and the method is applicable to popularization and application.
Owner:东莞市万酷电子科技有限公司

Gradient-based image restoration and enhancement

A gradient-based image enhancement and restoration method and system which applies an orientation-isotropy adaptive filter to the gradients of high structured regions, and directly suppresses the gradients in the noise or texture regions. A new gradient field is obtained from which image reconstruction can progress using least mean squares. The method generally comprises: inputting image data; calculating image gradients; defining the gradients as having large or small coherence; filtering the large coherence gradients for edge enhancement; suppressing the small coherence gradients for noise reduction; assembling an enhanced gradient field from the filtered large coherence and suppressed small coherence gradients; and optimizing the assembled gradient field into a restored image.
Owner:SIEMENS MEDICAL SOLUTIONS USA INC

Image restoration method based on image segmentation, and system therefor

InactiveCN101661613AOvercoming the matching phenomenonGuaranteed Priority Patching OrderImage enhancementImage analysisMean-shiftDecomposition
The invention discloses an image restoration method based on image segmentation, and a system therefor; the method comprises: firstly, manually selecting and marking the area to be restored in image by a user; then, carrying out image domain decomposition by mean shift algorithm, and dividing the image into a number of areas; finally, carrying out repeated iterative operation on the area to be restored until all pixels in the area to be restored is filled to be full. The method optimizes the calculation of priority in image restoration algorithm, thus effectively preventing the over expansionof the restored image from a high-texture area to a low-texture area; furthermore, matched block searching standard based on the image domain decomposition can be formulated on that basis, so that anerroneous block can be avoided being introduced; compared with the original image restoration method based on the sample, the effect of the method is more in accordance with the visual expectation ofhuman beings; furthermore, at present, the method is successfully applied to large size area restoration of various images with complex texture and structural characteristics as well as the aspects such as wiping off characters, removing target objects and the like.
Owner:BEIJING JIAOTONG UNIV
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