Local regression based colorization coding

A new image coding technique for color image based on colorization method is proposed. In colorization based image coding, the encoder selects the colorization coefficients according to the basis made from the luminance channel. Then, in the decoder, the chrominance channels are reconstructed by utilizing the luminance channel and the colorization coefficients sent from the encoder. The main issue in colorization based coding is to extract colorization coefficients well such that the compression rate and the quality of the reconstructed color becomes good enough. In this paper, we use a local regression method to extract the correlated feature between the luminance channel and the chrominance channels. The local regions are obtained by performing an image segmentation on the luminance channel both in the encoder and the decoder. Then, in the decoder, the chrominance values in each local region are reconstructed via a local regression method. The use of the correlated features helps to colorize the image with more details. The experimental results show that the proposed algorithm performs better than JPEG and JPEG2000 in terms of the compression rate and the PSNR value.