In our proposed system the random noise present in hyper spectral image is removed by means of tensor based decomposition methods. The noises present in hyper spectral images are classified into two categories namely: signal independent noise and signal dependent noise. The noises present in the hyper spectral images have dependence on the noise variance of the signal. The input image is separa...

Multi temporal aerial photography and airborne hyper spectral imagery have been integrated for the detection and monitoring of coal mining subsidence hazards. Digital elevation models derived from successive epochs of aerial photography provide estimates of topographic change which may be indicative of the collapse of abandoned underground mine workings in the study area. Ground disturbed by su...

This paper proposed an efficient method for contrast enhancement of real world hyper spectral images. The contrast of image is an important characteristic by which the quality of image can be judged as good or poor quality. The proposed method is consists of two stages: In first stage the poor quality of image is process by automatic contrast adjustment in spatial domain and in second stage the...

Abstract When observing targets in the near-Earth space environment using ground-based telescopes, Earth’s turbulent atmosphere and telescope’s aperture combine to act as a low-resolution spectrometer. The light at disparate wavelengths from given point object lands different spatial locations focal plane. Here we investigate feasibility of capitalizing on this effect provide snapshot hyper-spe...

An important aspect of spectral image analysis is identification of materials present in the object or scene being imaged. Since multi-spectral or hyper spectral imagery is generally low resolution, it is possible for pixels in the image to contain several materials. A paramount issue in image processing area is to design and implement an efficient segmentation and classification techniques dem...