Wireless Capsule Endoscopic Image Enhancement Method Based on Histogram Correction and Unsharp Masking in Wavelet Domain Due to the limited illumination and complex environment in the gastrointestinal (GI) tract, endoscopic images are usually not clear enough to be interpreted by doctors or used for further processing. In order to solve this problem, a method based on histogram correction and unsharp masking in the wavelet domain is proposed in this paper, to improve the contrast and reveal details of endoscopic images. The HSI color space is adopted for color naturalness, and a logarithm based histogram correction method (LHCM) is proposed to improve the contrast and avoid aritifacts. Details are further enhanced by unsharp masking. Experimental results show that performance of the proposed method is better compared with the stateofart methods. It can be applied to general images and have good effects as well.

Research on a New Feature Detection Algorithm for Wireless Capsule Endoscope Bleeding Images Based on Superpixel Segmentation Gastric hemorrhage is the manifestation of many digestive tract diseases. The traditional gastroscope detection has the disadvantages of insecurity, discomfort and unsanitary. As a new type of detection technology, wireless capsule endoscope (WCE) overcomes the defects of traditional gastroscope detection. But in the process of detection, due to the frequency of 2 frames per second, a huge amount of pictures will be generated. It is unreasonable to rely on doctors to manually screen images of gastric bleeding from massive pictures. Therefore, there is an urgent need for a high standard of computeraided medical technology. Based on this purpose, our paper proposes a new detection feature, the RG coefficient of variation of superpixel block, which is used to automatically detect gastric hemorrhage. Firstly, the superpixel segmentation method SLIC is used to segment the images, which preserves the homogeneity and edge information of the pixels in the region. Secondly, the new detection features are extracted from the super pixel blocks, compared to the traditional color features and the currently widely used color detection features. Kfold cross validation is performed on our data set. Finally, by using the new detection features proposed in our paper, the accuracy of the detection is improved by 4.13%, the sensitivity is improved by 7.5% and the miss detection rate is actually reduced. Achieve the automatic screening of suspicious bleeding images under the condition of ensuring high standards, and reduce the diagnosis time.