Demosaicing based Image Compression with Channel-wise Decoder



In this paper, we propose an image compression scheme which uses a demosaicking network and a channel-wise decoder in the decoding network. For the demosaicing network, we use as the input a colored mosaiced pattern rather than the well-known Bayer pattern. The use of a colored mosaiced pattern results in the mosaiced image containing a greater amount of information pertaining to the original image. Therefore, it contributes to result in a better color reconstruction. The channel-wise decoder is composed of multiple decoders where each decoder is responsible for each channel in the color image, i.e., the R, G, and B channels. The encoder and decoder are both implemented by wavelet based auto-encoders for better performance. Experimental results verify that the separated channel-wise decoders and the colored mosaic pattern produce a better reconstructed color image than a single decoder. When combining the colored CFA with the multi-decoder, the PSNR metric exhibits an increase of over 2dB for three-times compression and approximately 0.6dB for twelve-times compression compared to the Bayer CFA with a single decoder. Therefore, the compression rate is also increased with the proposed method than with the method using a single decoder on the Bayer patterned mosaic image.


1. Introduction
2. Preliminaries
2.1 Autoencoder based Compression Framework
2.2 Mosaicing as a Tool for Compression
3. Proposed Method
3.1 Mosaicing with Colored Mosaic Pattern
3.2 Usage of a Multi-Decoder
3.3 Architecture of the Proposed Method
4. Experimental Results
5. Conclusion


  • Indra Imanuel Doctoral Degree Candidate, Dept. Computer Engineering, Dongseo University, Korea
  • Suk-Ho Lee Professor, Dept. Artificial Intelligence Appliance, Dongseo University, Korea


자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 기관로그인 시 무료 이용이 가능합니다.

      • 4,000원

      0개의 논문이 장바구니에 담겼습니다.