Peking University

Beijing Founder Electronics Co., Ltd.

Jiaying Liu

Zongming Guo

Jie Ren

Yue Zhuo

Mading Li

Yue Zhou

Zhihui Zheng

Lieseng Yang

An image interpolation method and device based on an autoregressive model. The method first, interpolating a low-resolution image up to a target scale to obtain an interpolated image M; determining a local area W in the image M to be interpolated, establishing two autoregressive models for each pixel point in the local area W except for the edge pixel points, and determining an initial objective function F0 according to the autoregressive models; down sampling the local area W except for the edge pixel points to the same size as the low-resolution image to obtain a local area W', subtracting a corresponding area in the low-resolution image from W&#x2032; one pixel value by one pixel value, and adding the result to the initial objective function F0 to obtain an objective function F; performing iteration on the objective function F to obtain a pixel point value of a center block of W.

Image interpolation method and device based on autoregressive model

The present disclosure provides a non-local mean-based video denoising method, so as to remove illumination variation in a video by using image histogram specification filtering processing. The present disclosure further provides a non-local mean-based video denoising apparatus. The apparatus comprises a filtering module used for remove illumination variation in a video by using image histogram specification filtering processing. In the present disclosure, self-adaptive adjustment can be carried out on a change of an illumination condition.

Non-local mean-based video denoising method and apparatus

The present invention relates to the field of digital image enhancement technologies, and more particularly to a non-locality-based super-resolution reconstruction method and device, so as to solve the problem of relatively low resolution of an image after non-locality-based super-resolution reconstruction in the prior art. The method in the embodiment of the present invention comprises: determining a position of a search window where a current macro-block is mapped in each of other image frames; determining a search window where the current pixel block is mapped in the each of the image frames, according to the position of the search window where the macro-block, where the pixel corresponding to the current pixel block is located, is mapped in the each of the image frames, and determining a similarity value of each determined pixel block in the determined search window relative to the current pixel block respectively; and determining an optimized central pixel value of each pixel block according to the determined similarity value. By use of the embodiments of the present invention, the resolution of an image subjected to non-locality-based super-resolution reconstruction is enhanced.

Nonlocality based super resolution reconstruction method and device

A method for selecting the best mode of intra prediction coding for video coding applied in video coding and decoding field is provided. The method includes: constructing a rate distortion cost function based on an estimated rate to be encoded; computing the rate distortion costs for all predictive modes by using the constructed function, and selecting the predictive mode with the minimum rate distortion cost as the best mode of intra prediction coding according to the computing result. Accordingly, a device for selecting the best mode of intra prediction coding for video coding is provided. By the method, the selected mode is closer to the best mode selected by original rate distortion optimization model, thereby the need to code every block actually in the process of rate distortion optimization is effectively avoided.

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Beijing, China

Jiaying Liu