167 results about "Quantization (image processing)" patented technology

The invention belongs to the field of computer vision. In order to achieve the balance between general quantization error and overload error to ensure that the quantization output noise-signal ratio is optimum, the method adopts the technical scheme of a depth calculation imaging method based on a flight time TOF camera, and the method comprises the following steps: firstly, obtaining respective internal parameters including focal distances and optical centers and external parameters including rotation and translation of the TOF camera and a color camera after camera calibration, and obtaining a plurality of depth scatters on a high resolution diagram; secondly, building an autoregression model item of an energy function; thirdly, building an basic data item and a final solve equation of the energy function, building a data item of the energy function through an initial depth scatter diagram, and combining the data item and an autoregression item with a factor Lambada into a whole body to be served as a final solve equation through a lagrange equation; and fourthly, performing solving on an optimized equation through a linear function optimization method. The method is mainly applied to digital image processing.

The image processing method comprises: a recording failure position determination step of determining a recording failure position on an image corresponding to a malfunctioning recording element; a basic threshold value matrix storage step of storing a basic threshold value matrix set with threshold values used for halftoning of converting multiple-value input image data into dot data of a number of tonal graduations smaller than that of the multiple-value input image data by quantizing the multiple-value input image data; a sub-matrix storage step of storing a plurality of sub-matrices in association with recording failure positions in the basic threshold value matrix, each of the sub-matrices being set with threshold values which are substituted for the threshold values in a partial region of the basic threshold value matrix, the partial region including a pixel position corresponding to the recording failure position and having a width of a prescribed number of pixels; a replacement region determination step of determining a corresponding region with the width of the prescribed number of pixels including the recording failure position in the basic threshold value matrix, according to the pixel position in the input image data and the recording failure position determined in the recording failure position determination step; a sub-matrix selection step of selecting one of the sub-matrices stored in the sub-matrix storage step to use for substituting for the corresponding region determined in the replacement region determination step; a threshold value replacement step of creating a reformed threshold value matrix by replacing the threshold values of the corresponding region including the recording failure position in the basic threshold value matrix, with the one of the sub-matrices selected in the sub-matrix selection step; and a quantization processing step of quantizing the input image data by selectively using the basic threshold value matrix and the reformed threshold value matrix.

The invention relates to the technical field of image processing, in particular to an unmanned aerial vehicle tracking method based on a twin neural network and an attention mechanism, which is applied to continuously tracking a visual single-target unmanned aerial vehicle. According to the method, weight redistribution of channel attention and space attention is realized by using two attention mechanisms, and the representation capability of the model on an unmanned aerial vehicle target appearance model is enhanced by using an attention model for template branches of a twin network; and search images are preprocessed in a multi-scale zooming mode, response graph calculations are separately carried out, inverse transformation of scale changes of the unmanned aerial vehicle in a picture issimulated in the mode, search factors capable of generating larger response values serve as scale inverse transformation of the unmanned aerial vehicle so as to correct the size of a frame used for marking a target, and the transverse-longitudinal proportion of the frame is not changed. According to the method, the tracking precision of 0.513 is obtained through testing (the average coincidence rate is used as a quantization precision standard), and compared with other leading-edge tracking methods, the method has the advantage that the performance is obviously improved.

Provided is quantization processing that can reduce color development defect due to dot overlapping and can output an image with reduced granularity when the image is printed by using multiple kinds of colorants. To this end, dot arrangement information for a colorant for which dot arrangement is already determined among multiple kinds of colorants is acquired for a predetermined region of the image, and an evaluation value of each pixel included in the predetermined region is derived based on the arrangement information. In addition, for the predetermined region, a target value for a predetermined colorant for which dot arrangement is yet to be determined is derived based on the image. Then, whether or not to arrange a dot of the predetermined colorant in the predetermined region is determined based on the target value and the evaluation value.

A method for image compression of a set of image data includes performing a quantization operation on the image data. The quantization operation may include controlling a compression factor by applying a scaled quantization level obtained by multiplying a first quantization level by a gain factor. The gain factor may be updated as a function of a bit per pixel value of a compressed image. The update operation may include an iterative procedure including at least one iteration step that provides for updating a current gain factor as a function of a previous gain used for performing a previous compression step and as a function of a ratio of the bit per pixel value of the compressed image at the previous compression step to a target bit per pixel value. The method may be used in Joint Photographic Experts Group (JPEG) image processing and digital still cameras.

The invention belongs to the technical field of digital image processing, particularly relates to an image compression method, system and device based on code rate control of sparse coding, and aims to solve the problems of low remote sensing image compression efficiency and low image reconstruction quality after compression due to the fact that the existing remote sensing image compression code rate is not easy to control and the code rate distribution is unreasonable. The method comprises the following steps: dividing a to-be-coded image into set sizes, and setting coding parameters; extracting an image block mean value and carrying out quantization and entropy coding; after the actual coding rate of the image is updated each time, comparing the actual coding rate with a set target coderate, and determining the next operation according to the comparison result; in each iterative encoding process, selecting image blocks with high complexity for sparse encoding, and jointly determining the number of the image blocks by the actual encoding rate of the current image, the set target code rate and the coefficient; and completing image coding at a set coding rate. The coding rate is accurate and controllable, distribution is reasonable, dynamic adjustment can be achieved, and efficient and high-quality compression of images can be achieved.