JOURNAL ARTICLE

<title>Proposed radiology image lossy compression standard</title>

Dennis L. Wilson

Year: 1996 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2707 Pages: 273-283   Publisher: SPIE

Abstract

Radiology uses large images and series of images that can consume large amounts of storage or of communication bandwidth in the utilization of those images. An update to the standard for compressing radiology images is being considered by the medical imaging compression standards committee. A standard for compression of radiology images is proposed for consideration. The proposed standard uses four basic techniques to achieve very high quality reconstructed images: (a) image decomposition into high frequency and low frequency elements, (b) lapped orthogonal discrete cosine transforms, (c) local quantization, and (d) Huffman encoding. Degenerate forms of the standard include the JPEG standard, already included in the DICOM medical image interchange standard. The proposed standard is a departure from the JPEG standard because of the low quality of the baseline JPEG lossy compression. At the same time, much of the hardware and software that have been used for JPEG compression are applicable to the proposed standard technique. A preprocessing step changes the format of the image to a form that can be processed using JPEG compression. A post-processing step after the JPEG restoration will restore the image. The proposed standard does not permit many techniques that have been used in the past. In particular, decomposition by the level of the significant bits is not permitted, the only transform permitted is the lapped orthogonal discrete cosine transform, the block size of the transform is limited to 8 by 8, and only Huffman coding is allowed. There are many variations that can be used in compression. This proposal allows some variations, but restricts many other variations in the interest of simplicity for the standard. The quality of the compression is very good. The extra complexity in the standard to allow more variations is not warranted.

Keywords:
JPEG Lossy compression DICOM Computer science Discrete cosine transform Huffman coding Lossless JPEG Lossless compression JPEG 2000 Image compression Data compression Transform coding Quantization (signal processing) Artificial intelligence Lapped transform Computer vision Image quality Image processing Image (mathematics)

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Lung Cancer Diagnosis and Treatment
Health Sciences →  Medicine →  Pulmonary and Respiratory Medicine
Medical Imaging Techniques and Applications
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging

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