Abstract: The field of remote sensing and image processing are constantly evolving in the last decade. At present there are many enhancement techniques which are used for remote sensing image processing. The contrast of remote sensing images is low, which may include various types of noises. In order to make full use of remote sensing image information, the original image has to be enhanced. This paper presents different technologies which are recently proposed for remote sensing image processing. These techniques overcome the limitations of conventional methods. This represent enhancement methods based on Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Multi-Scale Retinex, Singular Value, Adaptive Intensity Transformations, and Dual-Tree Complex Wavelet Transform (DT-CWT). These methods overcome the limitations of the existing methods. Different application area has different requirement for image enhancement. These techniques perform image enhancement in different areas a

• Publication Date: 13-Jun-2013
• DOI: 10.15224/978-981-07-6935-2-26
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Abstract: Mathematical Morphology provides systematic approach to analyze geometric Characteristic of signal or images, has been applied to many application such as Edge Detection, Object segmentation, noise suppression. Image segmentation is one of the most important categories of image processing. The watersheds transformation for image segmentation using mathematical morphology is widely used. When we use watershed transform is image, there is a serious cause of over segmentation. In this paper the proposed system has been applied to overcome the over segmentation problem by using improved segmentation and efficient technique for image segmentation using mathematical morphology

• Publication Date: 13-Jun-2013
• DOI: 10.15224/978-981-07-6935-2-27
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• Downloads: 0