Side information estimating method oriented to distributed coding and decoding of multimedia sensor network

Abstract

The invention provides a side information estimating method based on a discrete cosine transform (DCT) low-frequency coefficient in distributed coding and decoding of a multimedia sensor network, which is used for solving the problem of large data volume in video application. In the method, a DCT low-frequency coefficient in an ROI (Region of Interest) macroblock of a non-key frame is extracted for performing entropy coding and decoding, bidirectional motion estimation interpolation is performed on an ROI macroblock decoding end by using the received DCT low-frequency coefficient to generate ROI macroblock side information, and motion compensation frame interpolation (or extrapolation) is performed on a non-ROI region by using a decoded frame to generate non-ROI macroblock side information and further generate optimal non-key frame side information. Through the improvements, the code rate can be lowered, the quality of a decoded image is enhanced, the energy consumption of a sensor node is lowered, and the life cycle of a wireless sensor network is prolonged. Due to the adoption of the method provided by the invention, optimal side information can be obtained while the code rate is lowered, the quality of a decoded image is enhanced, the energy consumption of a sensor node is lowered, and the life cycle of a wireless sensor network is prolonged.

Description

technical field

[0001] The invention is a technical solution for multimedia data compression in wireless multimedia sensor networks (Wireless Multimedia Sensor Networks, WMSN). A side information estimation method based on discrete cosine transform low-frequency coefficients is adopted to reduce energy consumption of nodes as much as possible while improving the quality of decoded images, and belongs to the technical field of computer wireless communication. Background technique

[0002] In recent years, with the rapid development of wireless multimedia communication technology, some new video application requirements have begun to appear, such as: wireless PC cameras, mobile video phones, wireless video surveillance, wireless multimedia sensor networks, etc. In these new video applications, due to the limitations of power supply, storage capacity, computing power, and communication capabilities, wireless video terminals not only require low-complexity encoding, but also req...

Examples

Embodiment Construction

[0047] Based on the Wyner-Ziv distributed video coding scheme, this method extracts the intense motion area through the ROI judgment criterion and extracts the DCT low-frequency coefficients of the area for Huffman decoding and compression. The decoding end uses the decoded DCT low-frequency coefficients to perform bidirectional motion estimation. Perform DCT hash (discrete cosine transform low-frequency coefficient) motion interpolation to generate the best side information, and the rest of the area is based on LDPC distributed codec, thereby reducing the bit rate while improving the decoded image quality, reducing node processing and transmission energy consumption, Realize optimized video transmission and prolong the life cycle of the entire network.

[0048] This method is based on the Wyner-Ziv distributed video coding scheme, and divides the video sequence into two different frames: key frame (Key Frame, K frame) and Wyner-Ziv frame (WZ frame). The traditional JPEG codin...

technical field

[0001] The invention is a technical solution for multimedia data compression in wireless multimedia sensor networks (Wireless Multimedia Sensor Networks, WMSN). A side information estimation method based on discrete cosine transform low-frequency coefficients is adopted to reduce energy consumption of nodes as much as possible while improving the quality of decoded images, and belongs to the technical field of computer wireless communication. Background technique

[0002] In recent years, with the rapid development of wireless multimedia communication technology, some new video application requirements have begun to appear, such as: wireless PC cameras, mobile video phones, wireless video surveillance, wireless multimedia sensor networks, etc. In these new video applications, due to the limitations of power supply, storage capacity, computing power, and communication capabilities, wireless video terminals not only require low-complexity encoding, but also req...

Examples

Embodiment Construction

[0047] Based on the Wyner-Ziv distributed video coding scheme, this method extracts the intense motion area through the ROI judgment criterion and extracts the DCT low-frequency coefficients of the area for Huffman decoding and compression. The decoding end uses the decoded DCT low-frequency coefficients to perform bidirectional motion estimation. Perform DCT hash (discrete cosine transform low-frequency coefficient) motion interpolation to generate the best side information, and the rest of the area is based on LDPC distributed codec, thereby reducing the bit rate while improving the decoded image quality, reducing node processing and transmission energy consumption, Realize optimized video transmission and prolong the life cycle of the entire network.

[0048] This method is based on the Wyner-Ziv distributed video coding scheme, and divides the video sequence into two different frames: key frame (Key Frame, K frame) and Wyner-Ziv frame (WZ frame). The traditional JPEG codin...

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