Abstract: A method and a device for image matching are disclosed. The method includes acquiring a template image and a target image; acquiring a group of template features according to the template image; extracting a group of target features according to the target image; and according to template features and target features, calculating an degree of image similarity between the template image and each frame of target images, and using a target image with the maximum degree of image similarity as a matched image the template image. In the disclosed image-matching method and image-matching device, image matching is performed by means of respectively calculating an degree of image similarity between a template image and each target image according to a degree of image similarity between template features and target features, so that non-redundancy of features in an image matching process and correct image matching can be guaranteed, and the image matching accuracy can be improved.

Abstract: An image representation method and processing device based on local PCA whitening. A first mapping module maps words and characteristics to a high-dimension space. A principal component analysis module conducts principal component analysis in each corresponding word space, to obtain a projection matrix. A VLAD computation module computes a VLAD image representation vector; a second mapping module maps the VLAD image representation vector to the high-dimension space. A projection transformation module conducts projection transformation on the VLAD image representation vector obtained by means of projection. A normalization processing module conducts normalization on characteristics obtained by means of projection transformation, to obtain a final image representation vector.

Abstract: The present application provides a method and a device for super-resolution image reconstruction based on dictionary matching. The method includes: establishing a matching dictionary library; inputting an image to be reconstructed into a multi-layer linear filter network; extracting a local characteristic of the image to be reconstructed; searching the matching dictionary library for a local characteristic of a low-resolution image block having the highest similarity with the local characteristic of the image to be reconstructed; searching the matching dictionary library for a residual of a combined sample where the local characteristic of the low-resolution image block with the highest similarity is located; performing interpolation amplification on the local characteristic of the low-resolution image block having the highest similarity; and adding the residual to a result of the interpolation amplification to obtain a reconstructed high-resolution image block.

Abstract: A method and a device for extracting local features of a 3D point cloud are disclosed. Angle information and the concavo-convex information about a feature point to be extracted and a point of an adjacent body element are calculated based on a local reference system corresponding to the points of each body element. The feature relation between the two points can be calculated accurately. The property of invariance in translation and rotation is possessed. Since concavo-convex information about a local point cloud is contained during extraction, the inaccurate extraction caused by ignoring concavo-convex ambiguity in previous 3D local feature description is resolved.

Abstract: A method for video encoding based on an image super-resolution, the method including: 1) performing super-resolution interpolation on a video image to be encoded using a pre-trained texture dictionary database to yield a reference image; in which the texture dictionary database includes: one or multiple dictionary bases, and each dictionary basis includes a mapping group formed by a relatively high resolution image block of a training image and a relatively low resolution image block corresponding to the relatively high resolution image block; 2) performing motion estimation and motion compensation of image blocks of the video image on the reference image to acquire prediction blocks corresponding to the image blocks of the video image; 3) performing subtraction between the image blocks of the video image and the corresponding prediction blocks to yield prediction residual blocks, respectively; and 4) encoding the prediction residual blocks.

Abstract: A self-adaptive motion estimation module includes a macro block division unit, a macro block selection unit, a motion intensity judgment unit, and a motion estimation unit. A video frame to be encoded is divided into macro blocks by the macro block division unit. The macro block selection unit sequentially selects an image block in a video frame as the current image block. The motion intensity judgment unit determines a motion intensity of the current image block, and makes a self-adaptive selection of a motion estimation method for performing motion estimation on the current image block according to the motion intensity of the current image block. The motion estimation unit performs motion estimation on the current image block according to the motion estimation method selected by the motion intensity judgment unit. Before motion estimations are performed on the image blocks, motion intensities of image blocks are determined.

Abstract: A method and a device for post-processing depth/disparity maps adopt a strategy of combining edge information and segmentation information when detecting irregular edge regions. The method includes dividing a color image into super pixels when performing image segmentation on a color image; partitioning a grayscale range into a preset number of intervals, and for each super pixel, statistically obtaining a histogram of all the pixel points that fall within the intervals; determining, in a current super pixel, whether a ratio of the number of pixels contained in the interval having a maximum interval distribution value, to the total number of pixels in the current super pixel is less than the first threshold; and if so, further dividing the current super pixel using a color-based segmentation method. The disclosed method and device improve accuracy of color image division while ensuring image processing speed, thus improving detection accuracy of the irregular edge regions.

Abstract: A super-resolution image reconstruction apparatus based on a classified dictionary database. The apparatus can select, from a training image, a first local block and a corresponding second down-sampled local block, extract corresponding features and combine the features into a dictionary group, and perform classification and pre-training on multiple dictionary groups by using calculated values of an LBS and an SES as classification marks, so as to obtain a classified dictionary database of multiple dictionary groups with classification marks. During image reconstruction, local features of a local block on an image to be reconstructed are extracted, the LBS and SES classification of the local block is matched with the LBS and SES classification of each dictionary in the classified dictionary database, so that matched dictionaries can be rapidly obtained, and lastly, image reconstruction is performed on the image to be reconstructed by using the matched dictionaries.

Abstract: A method and apparatus for rapidly reconstructing a super-resolution image. In the method and apparatus for rapidly reconstructing a super-resolution image provided in the present application, an original image is processed at least by means of iterative backward mapping based on a texture structural constraint during reconstruction of a super-resolution image of the original image, so as to enhance texture details of the image, thereby improving the high-frequency detail quality of the super-resolution image.

Abstract: A method for video encoding based on a dictionary database, the method including: 1) dividing a current image frame to be encoded in a video stream into a plurality of image blocks; 2) recovering encoding distortion information of a decoded and reconstructed image of a previous frame of the current image frame using a texture dictionary database to obtain an image with recovered encoding distortion information, and performing temporal prediction using the image with the recovered encoding distortion information as a reference image to obtain prediction blocks of image blocks to be encoded; in which, the texture dictionary database includes: clear image dictionaries and distorted image dictionaries corresponding to the clear image dictionaries; and 3) performing subtraction between the image blocks to be encoded and the prediction blocks to obtain residual blocks, and processing the residual blocks to obtain a video bit stream.

Abstract: An AVS video compression encoding method, including: 1) obtaining an image to be encoded; 2) calculating an average luminance value of the image to be encoded; 3) extracting an attribute component from the image to be encoded, dividing the attribute component into a plurality of attribute blocks, obtaining a transformation coefficient of every frequency point in an attribute block, and calculating a first average transformation coefficient of every frequency point in all attribute blocks, and calculating a second average transformation coefficient of a frequency band by first average transformation coefficients of all frequency points in the frequency; and 4) obtaining a final weighted quantization coefficient by using the average luminance value of the image to be encoded and the second average transformation coefficient of every frequency band to correspondingly adjust an initial weighted quantization coefficient of every frequency band in the quantization matrix.

Abstract: A method for video encoding based on an image super-resolution, the method including: 1) performing super-resolution interpolation on a video image to be encoded using a pre-trained texture dictionary database to yield a reference image; in which the texture dictionary database includes: one or multiple dictionary bases, and each dictionary basis includes a mapping group formed by a relatively high resolution image block of a training image and a relatively low resolution image block corresponding to the relatively high resolution image block; 2) performing motion estimation and motion compensation of image blocks of the video image on the reference image to acquire prediction blocks corresponding to the image blocks of the video image; 3) performing subtraction between the image blocks of the video image and the corresponding prediction blocks to yield prediction residual blocks, respectively; and 4) encoding the prediction residual blocks.

Abstract: An arithmetic encoding-decoding method for compression of a video image block. The method includes an encoding process and a decoding process. The encoding process includes: 1) acquiring an information of an image block to be encoded; 2) extracting an encoding command of a weighted skip model; 3) acquiring an index of a reference frame according to the information of the image block to be encoded and the command of the weighted skip model, in which the reference frame includes a prediction block for reconstructing the image block to be encoded; 4) acquiring a context-based adaptive probability model for encoding; and 5) performing arithmetic encoding of the index of the reference frame and writing arithmetic codes into an arithmetically encoded bitstream according to the context-based adaptive probability model for encoding.

Abstract: A P frame-based multi-hypothesis motion compensation method includes: taking an encoded image block adjacent to a current image block as a reference image block and obtaining a first motion vector of the current image block by using a motion vector of the reference image block, the first motion vector pointing to a first prediction block; taking the first motion vector as a reference value and performing joint motion estimation on the current image block to obtain a second motion vector of the current image block, the second motion vector pointing to a second prediction block; and performing weighted averaging on the first prediction block and the second prediction block to obtain a final prediction block of the current image block. The method increases the accuracy of the obtained prediction block of the current image block without increasing the code rate.

Abstract: A coding method based on multi-hypothesis motion compensation for a P-frame, including: a) using neighboring coded image blocks as reference image blocks, adopting a motion vector of each reference image block as a first motion vector which points to a first prediction block; b) adopting the first prediction block corresponding to each reference image block as a reference value, and performing joint motion estimation on the current image block to acquire a second motion vector which points to a second prediction block; c) weighted averaging the first prediction block and the second prediction corresponding to each reference image block to acquire a third prediction block of the current image block, respectively; and d) calculating a coding cost corresponding to each reference image block to determine a final first motion vector, a final second motion vector, and a final prediction block of the current image block.