Like JPEG2000, this is based on
wavelet compression, and was finalised in 2008.
Khashman and Dimililer [15] have proposed a medical compression using a neural network with a Haar
wavelet compression with nine compression ratios and a supervised neural network that learns to associate the image intensity (pixel values) with a single optimized compression ratio.
The pressure data signal of NPW is transformed to wavelets and then
wavelet compression and denoising are performed, respectively, followed by the event detection algorithm.
introduced energy-aware distributed
wavelet compression algorithms for WSN.
It is these temporal and magnitude relationships between coefficients that are exploited by
wavelet compression algorithms, such as SPIHT.
The high-density TVG450 enables APAC-based broadcasters, network operators and video professionals to utilise the advantages of high-quality JPEG2000
wavelet compression and the choice of ATM, SDH and IP connectivity.
The large internal storage capacity, combined with efficient
wavelet compression, translates to a "window of opportunity" of up to 3 months of retrievable data.
Two popular block compression techniques are the JPEG (Joint Photographic Experts Group) standard and
wavelet compression. JPEG uses both Huffman and run length encoding schemas for compressing images to reduce the volume of data.