An Image Compression Technique Based on the Novel Approach of Colorization Based Coding
Shireen Fathima1, E Kavitha2
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In this paper, we formulate a method for the colorization-based coding problem . Previously, several colorization methods have been proposed to colorize grayscale images using only a few representative pixels provided by the user. An encoder extracts RP from an original color image and transmits RP and all luminance components (compressed by the conventional encoder) to a decoder. Then, the decoder restores a color image by colorization Obviously, to implement colorization-based coding, automatic RP extraction is required, and which extraction method is chosen determines the performance of the colorization-based coding method. In this paper the colorization-based coding problem is formulated into an optimization problem, i.e., an L1 minimization problem .By formulating the colorization-based coding into an L1 minimization problem, it is guaranteed that, given the colorization matrix, the chosen set of RP becomes the optimal set in the sense that it minimizes the error between the original and the reconstructed color image. We construct the colorization matrix that colorizes the image in a multiscale manner. Experimental results revealed that our method can drastically suppress the information amount (number of representative pixels) compared to conventional colorization based-coding and outperforms conventional colorizationbased coding methods as well as the JPEG standard and is comparable with the JPEG2000 compression standard, both in terms of the compression rate and the quality of the reconstructed color image.