Microsoft Technology Licensing, LLC

The Hong Kong University of Science and Technology

Bing Zeng

Shipeng Li

Feng Wu

Guobin Shen

Ya-Qin Zhang

Xiaoyan Sun

Hua Cai

Zixiang Xiong

Jingjing Fu

Ming Lei Liou

Ming Liou

Aspects of the subject matter described herein relate to image restoration for compressed images. In aspects, image restoration is accomplished by recovering spectral information from data corresponding to a compressed image. The spectral information is recovered using an algorithm to search through a solution space of possible solutions while constraints are imposed on the solution space to trim undesirable solutions from the space. An algorithm described herein may be iteratively applied to improve the quality of the recovered image.

Spectral information recovery for compressed image restoration with nonlinear partial differential equation regularization

It is known to represent a square block of an image which has a maximum horizontal or vertical extension N as N vectors each representing one column or row, and encode it using an N&#xd7;N discrete cosine transform matrix. We introduce a technique which transforms an input vector, or array, representing a portion of an arbitrarily-shaped object block in which the maximum horizontal or vertical extension is at most N, by adding to it additional padding elements, to produce a vector or array which can be encoded using an N&#xd7;N discrete cosine transform. The padding maximises the number of transformed elements which are zero. We propose encoding arbitrarily-shaped objects based on this padding technique.

Method and apparatus for coding an image object of arbitrary shape

A motion-compensated video encoding scheme employs progressive fine-granularity layered coding to encode macroblocks of video data into frames having multiple layers, including a base layer of comparatively low quality video and multiple enhancement layers of increasingly higher quality video. Some of the enhancement layers in a current frame are predicted from different quality layers in reference frames. The video encoding scheme estimates drifting errors during the encoding and chooses a coding mode for each macroblock in the enhancement layer to maximize high coding efficiency while minimizing drifting errors.

Drifting reduction and macroblock-based control in progressive fine granularity scalable video coding

A video encoding system performs packetization of FGS/PFGS encoded video bitstreams by selecting encoded bitstream segments for packetization based on an estimated total contribution to distortion reduction associated with each encoded bitstream segment. The selected bitstream segments are then packetized according to a packet-independence packetization strategy that minimizes inter-packet dependency.

Packetization of FGS/PFGS video bitstreams

It is known to represent a square block of an image which has a maximum horizontal or vertical extension N as N vectors each representing one column or row, and encode it using an N&times;N discrete cosine transform matrix. We introduce a technique which transforms an input vector, or array, representing a portion of an arbitrarily-shaped object block in which the maximum horizontal or vertical extension is at most N, by adding to it additional padding elements, to produce a vector or array which can be encoded using an N&times;N discrete cosine transform. The padding maximises the number of transformed elements which are zero. We propose encoding arbitrarily-shaped objects based on this padding technique.

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Hong Kong, China

Bing Zeng