Abstract
The quality of remotely sensed satellite images depends on the reflected electromagnetic radiation from the earth’s surface features. Lack of consistent and similar amounts of energy reflected by different features from the earth’s surface results in a poor contrast satellite image. Image enhancement is the image processing of improving the quality that the results are more suitable for display or further image analysis. In this paper, we present a detailed model for color image enhancement using the quaternion framework. We introduce a novel quaternionic frequency enhancement algorithm that can combine the color channels and the local and global image processing. The basic idea is to apply the α-rooting image enhancement approach for different image blocks. For this purpose, we split image in moving windows on disjoint blocks. The parameter alfa for every block and the weights for every local and global enhanced image driven through optimization of measure of enhancement (EMEC). Some presented experimental results illustrate the performance of the proposed approach on color satellite images in comparison with the state-of-the-art methods.
Highlights
The atmospheric influences and sensor characteristics result in a poor contrast on satellite images
In this type of contrast enhancement techniques, the global histogram information is considered for enhancement
Adaptive histogram equalization (AHE) is an image processing technique related to a non-uniform spatial improvement technique
Summary
The atmospheric influences and sensor characteristics result in a poor contrast on satellite images. Adaptive histogram equalization (AHE) is an image processing technique related to a non-uniform spatial improvement technique. This method does not work well with smooth areas and does not eliminate the noise gain in these areas [8]. One of the most popular modifications of AHE is the contrast limited adaptive histogram equalization (CLAHE) [9] This method has overenhancement resulting in the loss of some local information [10]. The color image enhancement approaches are based on the processing of each color channel (red, green, and blue) separately [14] This methodology fails to capture the inherent correlation between the components and results in color artefacts [14]. In this paper we proposed a novel enhancement technique using local and global processing and quaternion-based approach
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