Endoscopy is a process that allows viewing/ visualize the inside of a human body. In this article, we propose a specular reflection detection algorithm for endoscopic images that utilizes intensity, saturation and gradient information. The proposed algorithm is a two-stage procedure: (a) image enhancement using an adaptive alpha-rooting algorithm and (b) an efficient reflection detection algorithm in the HSV color space. The extensive computer simulations show a significant improvement over stateof-the-art results for specular reflection detection and segmentation accuracy.
This paper presents a new combined local and global transform domain-based feedback image enhancement algorithm for medical diagnosis, treatment, and clinical research. The basic idea in using local alfa-rooting method is to apply it to different disjoint blocks with different sizes. The block size and alfa-rooting parameters driven through optimization using the Agaian's cost function (image enhancement non-reference quality measure). The presented new approach allows enhancing MRI and CT images with uneven lighting and brightness gradient by preserving the local image features/details. Extensive computer simulations (CS) on real medical images are offered to gage the presented method. CS shows that our method improves the contrast and enhances the details of the medical images effectively compared with the current state-of-art methods.
We present a new image enhancement algorithm based on combined local and global image processing. The basic idea is to apply α-rooting image enhancement approach for different image blocks. For this purpose, we split image in moving windows on disjoint blocks with different size (8 by 8, 16 by 16, 32 by 32 and, i.e.). The parameter alfa for every block driven through optimization of measure of enhancement (EME). The resulting image is a weighted mean of all processing blocks. This strategy for image enhancement allows getting more contrast image with the following properties: irregular lighting and brightness gradient. Some experimental results are presented to illustrate the performance of the proposed algorithm.
The research problem is to find an effective enhancement method for enhancing raw underwater color images. In underwater, as depth increases the high wavelength regions of the light spectrum are absorbed by the water and the light spectrum consists only of low wavelength regions such as green and blue and therefore, the image captured underwater looks green or greenish blue. This paper proposes an enhancement algorithm for improving the quality of raw underwater images by the method of alpha-rooting by two-side 2-D quaternion discrete Fourier transform (QDFT) with color correction done by multiscale retinex (MSR). The results of proposed enhancement are compared with the alpha-rooting method, by transforming color images to 2-D grayscale images. The enhancement are measured with reference to the metric color enhancement measure estimation.