Differentiation Applied To Lossless Compression Of Medical Images

Lossless compression of medical images using a proposed differentiation technique is explored, This scheme is based on computing weighted differences between neighboring pixel values, The performance of the proposed approach, for the lossless compression of magnetic resonance (MR) images and ultrasonic images, is evaluated and compared with the lossless linear predictor and the lossless Joint Photographic Experts Group (JPEG) standard, The residue sequence of these techniques is coded using arithmetic: coding, The proposed scheme yields compression measures, in terms of bits per pixel, that are comparable with or lower than those obtained using the linear predictor and the lossless JPEG standard, respectively, with 8-b medical images, The advantages of the differentiation technique presented here over the linear predictor are: 1) the coefficients of the differentiator are known by the encoder and the decoder, which eliminates the need to compute or encode these coefficients, and 2) the computational complexity is greatly reduced, These advantages are particularly attractive in real time processing for compressing and decompressing medical images

Differentiation applied to lossless compression of medical images

Lossless compression of medical images using a proposed differentiation technique is explored. This scheme is based on computing weighted differences hetween neighboring pixel values. The performance of the proposed approach, for the lossless compression of magnetic resonance (MR) images and ultrasonic images, is evaluated and compared with the lossless linear predictor and the lossless Joint Photographic Experts Group (JPEG) standard. The residue sequence of these techniques is coded using arithmetic coding. The proposed scheme yields compression measures, in terms of bits per pixel, that are comparable with or lower than those obtained using the linear predictor and the lossless JPEG standard, respectively, with 8-b medical images. The advantages of the differentiation technique presented here over the linear predictor are: 1) the coefficients of the differentiator are known by the encoder and the decoder, which eliminates the need to compute or encode these coefficients, and 2) the computational complexity is greatly reduced. These advantages are particularly attractive in real time processing for compressing and decompressing medical images. © 1996 IEEE