With some applications there can be uncertainty as to what image features are important and how these would be affected by lossy image coding. For example, in critical medical applications, errors in a diagnosis or interpretation could be legally attributed to artifacts introduced by the imagecompres...
A new lossy-to-lossless quality-progressive method for image coding is presented. This method is based on binary tree decomposition and context-based arithmetic coding. Experimental results obtained with the eighteen 8-bit ISO images show that the proposed method attains an average lossless compression...
An alternative approach to lossless image compression, that has emerged recently is based on subband decomposition. There are several advantages offered by a subband approach for lossless image compression. The most important of which is perhaps the natural integration of lossy and lossless compression ...
In disease diagnosis, medical image plays an important part. Its lossless compression is pretty critical, which directly determines the requirement of local storage space and communication bandwidth of remote medical systems, so as to help the diagnosis
Efficient Lossy to Lossless Medical Image Compression Using Integer Wavelet Transform and Multiple Subband DecompositionSince medical imaging produce prohibitive amounts of data, efficient and low-complexity compression is necessary for storage and communication purposes. In this paper, a flexible coding ...
[IEEE 2018 IEEE MTT-S International Wireless Symposium (IWS) - Chengdu, China (2018.5.6-2018.5.10)] 2018 IEEE MTT-S International Wireless Symposium (IWS) - A general method for extending a lossy network to a lossless network using the matrix decomposition ...
It can be classified into three types. One is the lossless recovery, it means the recovered image is the same as the original one; another one is called ‘slightly lossy’ recovery, it mean that the PSNR value of the recovered image is near 40, other types are called lossy recovery. ...
In lossy compression, transform coding has demonstrated excellent performance, but most transforms are not directly applied to lossless compression systems. For example, the inverse discrete cosine transform (DCT) and inverse discrete Fourier transform (DFT) both lead to certain accuracy loss in transfor...
An adaptive method based on Singular Value Decomposition is significantly more complex, yet it is simpler than computing KLT for the image [31]. Certain images require lossless compression. Medical images are a typical example because lossy compression of various medical image modalities used for ...
KeWangSpringer Berlin HeidelbergZhang LB, Wang K. "Efficient Lossy to Lossless Medical Image Compression Using Integer Wavelet Transform and Multiple Subband Decomposition", Lecture Note in Computer Science, vol 3150, August 2004. pp: 86-93.