Image compression: Maxshift ROI encoding options in JPEG2000
Image compression can improve the performance of the digital systems by reducing time and cost in image storage and transmission without significant reduction of the image quality. Furthermore, the JPEG2000 has emerged as the new state-of-the art standard for image compression. In this paper, a Selective Coefficient Mask Shift (SCMShift) coding method is proposed. The technique, implemented over regions of interest (ROIs), is based on shifting the wavelet coefficients that belong to different subbands, depending on the coefficients relative to the original image. This method allows: (1) codification of multiple ROIs at various degrees of interest, (2) arbitrary shaped ROI coding, and (3) flexible adjustment of the compression quality of the ROI and the background. No standard modification for JPEG200 decoder was required. The method was applied over different types of images. Results show a better performance for the selected regions, when ROI coding methods were employed for the whole set of images. We believe that this method is an excellent tool for future image compression research, mainly on images where ROI coding can be of interest, such as the medical imaging modalities and several multimedia applications.
keywords: Image coding, JPEG2000, Region of interest, Wavelet coding
Publication: Congress
1624015015660
June 18, 2021
/research/publications/image-compression-maxshift-roi-encoding-options-in-jpeg20002
Image compression can improve the performance of the digital systems by reducing time and cost in image storage and transmission without significant reduction of the image quality. Furthermore, the JPEG2000 has emerged as the new state-of-the art standard for image compression. In this paper, a Selective Coefficient Mask Shift (SCMShift) coding method is proposed. The technique, implemented over regions of interest (ROIs), is based on shifting the wavelet coefficients that belong to different subbands, depending on the coefficients relative to the original image. This method allows: (1) codification of multiple ROIs at various degrees of interest, (2) arbitrary shaped ROI coding, and (3) flexible adjustment of the compression quality of the ROI and the background. No standard modification for JPEG200 decoder was required. The method was applied over different types of images. Results show a better performance for the selected regions, when ROI coding methods were employed for the whole set of images. We believe that this method is an excellent tool for future image compression research, mainly on images where ROI coding can be of interest, such as the medical imaging modalities and several multimedia applications. - Tahoces PG, Varela JR, Lado MJ, Souto M - 10.1016/j.cviu.2007.07.001
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