Introduction to data compression (2nd ed.)
Introduction to data compression (2nd ed.)
Digital Image Compression Techniques
Digital Image Compression Techniques
Perception of computer simulated pulmonary lesions in chest radiographs
ACM '72 Proceedings of the ACM annual conference - Volume 1
Color image compression: early vision and the multiresolution representations
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Lossy compression of noisy images
IEEE Transactions on Image Processing
Wavelet-based color image compression: exploiting the contrast sensitivity function
IEEE Transactions on Image Processing
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This paper addresses two questions concerning JPEG2000 compression – firstly – how much has noise influence on compression performance – secondly – can compression performance be improved by applying a new complementary conception with introducing a denoising process before the application of compression Indeed, radiographic images are a combination between the relevant signal and noise, which is per definition not compressible. The noise behaves generally close to a mixture of Gaussian and/or Poisson statistics, which generally affects the compression performance. In this paper, the influence of noise on the compression performance of JPEG2000 images with investigating the parameters signal dynamic and spatial pattern frequency are considered; and the JPEG2000 compression scheme combined with a denoising process is analyzed on simulated and real dental ortho-pan-tomographic images. The test images are generated using Poisson statistics; the denoising utilizes a Monte Carlo noise modeling method. A hundred selected images are denoised and the compression ratio, using lossless and lossy JPEG 2000, is reported and evaluated.