The Applications of Improved Retinex Algorithm for X-Ray Medical Image Enhancement

Abstract

The vision is the only way that people receives image information. Retinex is the theory and method of image enhancement that is based on experiments and analysis of vision. Retinex enhances the image by processing reflection R and incident light L from the image S to obtain better vision quality. It is described that the image appears to reflect or transmit more or less of the light, varying from black to white for image and from black to colorless for transparent volume in this paper. The calculation shows the improvement of global and local image enhancement by Retinex algorithm for X-Ray medical images. Finally the analysis and comparison by experiments are discussed.

HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter

“…Reference [6] enhanced the pathological anatomy images based on superresolution to improve medical diagnosis. In recent years, the Retinex theory is widely used in the medical image processing [7]. Many algorithms based on Retinex theory such as single-scale Retinex (SSR) [8], multiscale Retinex (MSR) [9], McCann99 [10], and Frackle-McCann [11] have been developed for image enhancement.…”

Color Image Enhancement Using a Retinex Algorithm with Bilateral Filtering for Images with Poor Illumination

“…It focuses on processing an image to bring out important hidden features. Generally, medical microscopy and real-world images often suffer from poor contrast or lack of detail [1][2][3][4]. Thus, image-enhancement techniques are used to manipulate the original images to obtain better results for further image processing and analysis.…”

Weighted Retinex algorithm based on histogram for dental CT image enhancement

“…Recently, much attention has been paid to the Retinex method [1], [2], [8]. Retinex is a model about the Human Visual System that how to adjust and percept the color and brightness of the object [8].…”

“…Retinex is a model about the Human Visual System that how to adjust and percept the color and brightness of the object [8]. It tries to soften the strongest edges, keep the faint edges almost untouched, flatten the gap between the local bright and dark region and provide with a better perception effect [9].…”