A Least-squares Adapted Algorithm with Edge-look-ahead for Lossless Compression of Image Sequences

碩士 === 國立臺北科技大學 === 電腦與通訊研究所 === 100 === With the advances in medical technologies, medical imaging has been widely applied in clinical medicine. In order that the captured images can be exchanged and analyzed between the medical equipment and the host computer, a so-called digital imaging and commu...

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Bibliographic Details
Main Authors: Yen-Jun Chou, 周彥榕
Other Authors: Lih-Jen Kau
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/y5xf9w
Description
Summary:碩士 === 國立臺北科技大學 === 電腦與通訊研究所 === 100 === With the advances in medical technologies, medical imaging has been widely applied in clinical medicine. In order that the captured images can be exchanged and analyzed between the medical equipment and the host computer, a so-called digital imaging and communications in medicine (DICOM) protocol is developed for the transfer of digital medical images. On the other hand, a large storage capacity is usually required for medical images for its large dimension and high resolution. Therefore, lossless image compression technique is usually required for efficient storage of medical images and sequences. Aimed to provide an efficient algorithm for the compression of medical image sequences, we propose in this paper a coding scheme that can switch between two prediction modes; the intra mode coding scheme and the inter mode coding scheme. For intra mode coding, a Least-squares-based adaptive predictor is applied for the removal of spatial redundancy. Moreover, the predictor coefficients are adapted whenever an edge or a boundary is detected so that a large prediction error and the high computational cost of LS adaptation process can be avoided. For inter mode coding, a fast motion estimation algorithm is applied for the removal of temporal redundancy. Moreover, the decision of using an intra or inter mode is mainly based on the correlation between consecutive image sequences. Experimental results show that the proposed algorithm can have a very good compression ratio as well as a very good run-time performance, which justifies the usefulness of the proposed approach for the compression of medical image sequences.