| Pub. Date | : Oct, 2018 |
|---|---|
| Product Name | : The IUP Journal of Electrical and Electronics Engineering |
| Product Type | : Article |
| Product Code | : IJEEE11810 |
| Author Name | : Manish Kumar Saini and Sumit Saini |
| Availability | : YES |
| Subject/Domain | : Management |
| Download Format | : PDF Format |
| No. of Pages | : 14 |
The paper proposes local information-based contrast enhancement, which exploits the local information of the image extracted from sub-images of the color image. The number of sub-images or, in other words, the level of local information is optimized using wild goat algorithm to achieve the maximum contrast enhancement. Division of image into sub-images prior to applying the enhancement technique facilitates the enhancement of small blocks to prevent underexpose or overexpose in images, which usually results when any enhancement technique is applied over the complete image uniformly. The proposed technique performs stretching of histogram of small sub-images according to fuzzy logic having average intensity of sub-image as its input. The number of sub-images is optimized by wild goat algorithm with performance measures, i.e., Tenengrad and CII as the cost function. The proposed technique performs better than histogram equalization and conventional fuzzy-based methods.
In the field of image processing, there are many problems which hinder the effective analysis of images. Some of the issues are dim lighting, motion while capturing, different aperture sizes, nonlinear mapping of image information which is visible on the shapes and range of the histogram. All these problems are due to limited range of image capturing devices and result in poor image contrast, focusing on the need for contrast enhancement techniques. Many engineering domains like robotics, biomedical, surveillance, defense etc. need the advance contrast enhancement techniques. Sometimes, the important information gets missed due to motion while capturing the device. This information gets regained by the contrast enhancement techniques improving the appearance of original color image. Different factors decide the visual appearance of the image, e.g., background, color, etc. (Kim, 1995; Bendoumi et al., 2014; and Gonzalez, 2014). One of the primary factors of the image is its contrast which has a major role in impacting its visual appearance and reception of maximum information out of this image. The paper presents the novel technique for contrast enhancement of the color images using the local information of the image being analyzed using fuzzy logic, optimized by Wild Goat (WG) optimization algorithm.
Optimization, Fuzzy logic, Contrast enhancement