Image Segmentation Based Graph-Cut Approach to Fast Color Image Coding via Graph Fourier Transform

• Published in: Visual communications and image processing (Online) pp. 1 - 4
• Main Authors: Abiko, Kaito, Uruma, Kazuniri, Sugawara, Mamoru, Hangai, Seiichiro, Hamamoto, Takayuki
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.12.2019
• Subjects: Color; colorization; Decoding; fast algorithm; Fourier transforms; graph Fourier transform; Image coding; image compression; Image segmentation; Laplace equations; Signal processing algorithms; signal processing on graphs
• ISSN: 2642-9357
• DOI: 10.1109/VCIP47243.2019.8966021

Colorization-based image coding is a technique to compress chrominance information of an image using a colorization technique. The conventional algorithm applies graph Fourier transform to the colorization-based coding. In this algorithm, several pixels on the image are defined as vertices of the graph, and the chrominance values of that pixels are set as graph signals. Then, the graph signal corresponding to the several chrominance values on the image is transformed to the graph spectrum based on the graph Fourier transform, and the graph spectrum is compressed and stored. Because the stored graph spectrum gives the graph signal on the image based on the inverse graph Fourier transform in decoding phase, the color image is recovered from the luminance image and the several chrominance values corresponding to the graph signal. However, high calculation time is required to perform graph Fourier transform, and therefore, this paper proposes a fast graph Fourier transform to improve the conventional colorization-based image coding algorithm. In numerical examples, although the PSNR value is decreased 0.3 dB, the proposed algorithm is 16.8 times faster than the conventional method.