Blocking effect reduction of VQ-compressed images using neural network filter and DSP implement
Zhongren Liu, Sheng-He Sun, Yigang Zhang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
VQ technology has been proved to be an important technology and are extensively used in the low-bit-rate image compression. The VQ quantizer consists of two procedures: an encoder and a decoder. The encoder assigns each input vector X to an index i, which points to the closest codeword Yi in the codebook. The decoder uses the index i to look up the codeword 1', in the codebook. With good designed coodbook, the VQ quantizer can obtain very low bit rate compressed image while the decoded images have high SNR. The VQ also leads to blocking effect which is not comfortable to naked eye. To smooth the decoded image, some image filters for color image are studied here. Linear filter, such as scalar/vector mean filter, can not fulfill the target. The nonlinear filter, such as scalar median filter, vector median filter and vector direction filter can do better work. The neural network image filter proposed in this paper has a forward structure. This filter is optimized with advanced GA method. Then this filter is applied to color image filter and have a better performance. The parallel structure makes it easy to implement on the DSP device. Both VQ encoder/decoder and NN image filter are implemented on the fastest DSP, TI TMS320C6416.