Effects of 3D wavelets and KLT-based JPEG-2000 hyperspectral compression on exploitation

Low-complexity compression of multispectral images based on classified transform coding

“…In fact, transform coding techniques are well established and deeply understood, they provide excellent performances in the compression of images, video and other sources, have a reasonable complexity and, not least, are at the core of well-known and efficient standards such as JPEG and JPEG2000, implemented in coders widely used and easily available to the scientific community [16]. As a matter of fact, a common approach for coding multispectral images [14,11] is to use some decorrelating transforms along the spectral dimension followed by JPEG2000 on the transform bands with a suitable rate allocation among the bands. Viable alternatives include the use of wavelet transform (WT) followed by SPIHT [3,15], schemes based on the more traditional discrete cosine transform (DCT) [12,1], or on other application-oriented transforms, e.g., [4].…”

Effects of Lossy Compression of Hyperspectral Imagery

“…Lossy compression and background classification are somewhat alike in the sense that compression tends to preserve coarse features and discard fine ones, and classification tends to classify together spectra that are roughly similar but might differ in their fine details. However, for a similar compression scheme, Shen and Kasner [26] reported "no appreciable degradation" for anomaly detection and material identification at compression ratios up to 48, the highest they tested.…”

“…Also, the energypreserving, energy-packing, and decorrelation properties always hold, and PCA/KLT often provides good compression performance for non-Gaussian data. PCA/KLT forms a crucial part of many HSI compression schemes [13,20,23,24,26], including ours.…”

“…In practice, Pchance is estimated from the empirical estimates Pr(C[x, y] = i) and Pr(Cref[x, y] = i) of (26) and (22).…”

“…Lossy compression then becomes necessary. Because lossy compression discards potentially useful information, researchers are interested in evaluating its effects on application performance [20,24,26]. This report employs a simple but effective lossy compression scheme and studies its effects on a number of applications, namely normalized difference vegetation index, integrated column water vapor, and background classification.…”