A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The JPEG still picture compression standard
Communications of the ACM - Special issue on digital multimedia systems
Image quality in lossy compressed digital mammograms
Signal Processing
Embedded image coding using zerotrees of wavelet coefficients
IEEE Transactions on Signal Processing
An image multiresolution representation for lossless and lossy compression
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Shape-adaptive discrete wavelet transforms for arbitrarily shaped visual object coding
IEEE Transactions on Circuits and Systems for Video Technology
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering
A generalization of quad-trees applied to image coding
Integrated Computer-Aided Engineering
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Progressive lossy to lossless image compression of region-of-interest (ROI) in digital mammograms ensures receiving data of high quality at early stages of the transmission process which can be very useful for handling mammograms in Picture Archiving and Communication Systems (PACS) and teleradiology systems. In this paper, ROI images corresponding to clustered microcalcification in digitized mammogram are compressed using wavelet based progressive lossy to lossless image compression scheme. The coding scheme is optimized by a proper selection of the combination of reversible wavelet transform filters' and starting bitplane level. The proposed algorithm is implemented and tested using several mammograms from the Mammographic Image Analysis Society (MIAS) database. The experimental results show that ROI- based image compression offers a high visual quality of compressed images at a very low bit rate (0.05 bpp), and the combination of the 2/6 integer wavelet transform and the starting of ROI coding at moderate bitplanes represents an optimal selection. For example, high compression (0.05 bpp) using the 2/6 transform with ROI coding starting at moderate bitplane produced compression results with a lower mean-square-error (MSE) than those obtained from the same transform with ROI coding starting at lower and higher bitplanes. Also, the visual quality of its compression results was better than those of the other transforms.