Digital Image Compression Techniques
Digital Image Compression Techniques
DCC '95 Proceedings of the Conference on Data Compression
Set redundancy, the enhanced compression model, and methods for compressing sets of similar images
Set redundancy, the enhanced compression model, and methods for compressing sets of similar images
The centroid method for compressing sets of similar images
Pattern Recognition Letters
Performing joins without decompression in a compressed database system
ACM SIGMOD Record
A comparison of set redundancy compression techniques
EURASIP Journal on Applied Signal Processing
Efficient compression of text attributes of data warehouse dimensions
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
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The volume of medical imaging data produced per year is rapidly increasing, overtaxing the capabilities of Picture Archival and Communication (PACS) systems. Image compression methods can lessen the problem by encoding digital images into more space-efficient forms. Image compression is achieved by reducing redundancy in the imaging data. Existing methods reduce redundancy in individual images. However, these methods ignore an additional source of redundancy, which is based on the common information stored in more than one image in a set of similar images. We use the term "set redundancy" to describe this type of redundancy. Medical image databases contain large sets of similar images, therefore they also contain significant amounts of set redundancy.This paper presents two methods that extract set redundancy from medical imaging data: the Min-Max Differential (MMD), and the Min-Max Predictive (MMP) methods. These methods can improve compression of standard image compression techniques for sets of medical images. Our tests compressing CT brain scans have shown an average of as much as 129% improvement for Huffman encoding, 93% for Arithmetic Coding, and 37% for Lempel-Ziv compression when they are combined with Min-Max methods. Both MMD and MMP are based on reversible operations, hence they provide lossless compression.