Abstract
This paper proposes a representative pixel (RP) extraction algorithm and chrominance image recovery algorithm for the colorization-based digital image coding. The colorization-based coding methods reduce the color information of an image and achieve higher compression ratio than JPEG coding; however, they take much more computing time. In order to achieve low computational cost, this paper proposes the algorithm using the set of multiple-resolution images obtained by colorization error minimizing method. This algorithm extracts RPs from each resolution image and colorizes each resolution image utilizing a lower resolution color image, which leads to the reduction of the number of RPs and computing time. Numerical examples show that the proposed algorithm extracts the RPs and recovers the color image fast and effectively.
Highlights
The image colorization technique can recover a full-color image from a luminance image and several representative pixels (RPs) which have the chrominance values and their positions [1–4]
Because the luminance image can be compressed by standard coding methods such as JPEG coding and because the chrominance information is represented by a small number of RPs, the colorization-based image coding can compress full-color images more than these methods
The performance of the colorization based coding is evaluated based on the number of RPs and the quality of a restore image, and the objective of this paper is to propose a new coding method which requires less RPs and gives more accurate chrominance information
Summary
The image colorization technique can recover a full-color image from a luminance image and several representative pixels (RPs) which have the chrominance values and their positions [1–4]. This paper proposes a new colorization-based image coding algorithm consisting of the extraction RPs phase (coding) and the colorization phase (decoding). In order to achieve a low computational cost and to reduce the amount of information to represent RPs, the algorithm extracts RPs from a set of multiple resolution images obtained by multiple downsampling and colorization error minimizing. The major contribution of this paper is to propose a colorizationbased image coding algorithm which requires less computational time and achieves a high coding performance.
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