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Abstract
The Eight-Scale parameter adjustment is a natural extension of Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm. It has long been known that the Human Vision System (HVS) heavily depends on detail and edge in the understanding and perception of scenes. The main goal of this study is to produce a contrast enhancement technique to recover an image from blurring and darkness, and at the same time to improve visual quality. Eight-scale coefficient adjustments can provide a further local refinement in detail under the AIHT algorithm. The proposed Eight-Scale Adaptive Inverse Hyperbolic Tangent (8SAIHT) method uses the sub-band to calculate the local mean and local variance before the AIHT algorithm is applied. This study also shows that this approach is convenient and effective in the enhancement processes for various types of images. The 8SAIHT is also capable of adaptively enhancing the local contrast of the original image while simultaneously extruding more on object details.
Highlights
In human visual perception, contrast has a significant influence on the quality of an image
The 8SAIHT is capable of adaptively enhancing the local contrast of the original image while simultaneously extruding more on object details
It lacks a mechanism to adjust the degree of enhancement; using the Adaptive Inverse Hyperbolic Tangent (AIHT)-based image contrast enhancement approach cannot retain the detail brightness distribution of the original image, leading to distortion
Summary
Contrast has a significant influence on the quality of an image. The global contrast stretching method is simple and powerful, but it cannot adapt to the local brightness features of the input image because it uses only global information over the whole image. This fact limits the contrast-stretching ratio in some parts of the image, and causes significant contrast losses in the background and other small regions. To overcome this limitation, this study proposes an Eight-Scale Adaptive Inverse Hyperbolic Tangent (8SAIHT) method. Test results indicate that the proposed method could provide better image contrast than conventional enhancement methods in terms of visual looks and image details
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