In: Prasad S, Bruce LM, Chanussot J (eds) Augmented vision and reality: optical remote sensing, vol 3. In: Proceedings of the society of photo-optical instrumentation engineers (SPIE), atmospheric and environmental remote sensing data processing and utilization: an end-to-end system perspective, vol 5548Ĭhristophe E (2011) Hyperspectral data compression tradeoff. Huang et al B (2004) Lossless data compression for infrared hyperspectral sounders-an overview. In: Motta G, Storer J (eds) Hyperspectral data compression. Ramakrishna B et al (2006) Spectral/spatial hyperspectral image compression. IEEE J Select Top Appl Earth Obs Remote Sens 7(6 ):2246–2255 Huber-Lerner M, Hadar O, Rotman SR, Huber-Shalem R (2014) Compression of hyperspectral images containing a subpixel target. The quality of image is going to be calculated using the mean square error and peak signal-to-noise ratio value. The popular known Reed–Xiaoli algorithm is used for the identification of the current pixels with the background image. We are proposing this method in combination pattern to reduce the data dimensionality without loss of data, but as DCT is lossy type of compression, we are going to use DCT to just find the coefficient of the image. We introduced a method known as PCA–DCT method for compression which means principal component analysis followed by discrete cosine transform. To overcome such problem, a unique compression method should be there to compress the image with less data loss and low transmission period. Different types of compression methods had been performed on this type of image to compress and to reduce storage size and time. Hence, compression of such image is very important to reduce the size and transmission time. As this type of images is of large data, they possess large amount of storage size and transmission time is also much as compare to other image. To capture the hyperspectral image, different types of sensor are used in satellite such as AURA, CALIPSO, OCO, and PARASOL, whereas hyperspectral image sensors are used to measure the reflectance of each pixel value in very large amount and stored in 3D cube format. Hyperspectral image is a high-resolution image containing large number of details about the presented region.
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