An improved image enhancement algorithm

详细信息    查看全文

• 作者：Jing Ma ; Chengming Zou ; Xiaolong Jin
• 关键词：successive mean quantization transform (SMQT) ; Otsu algorithm ; optimal threshold ; image enhancement
• 刊名：Wuhan University Journal of Natural Sciences
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：22
• 期：1
• 页码：85-92
• 全文大小：
• 刊物类别：Mathematics and Statistics
• 刊物主题：Life Sciences, general; Materials Science, general; Computer Science, general;
• 出版者：Wuhan University
• ISSN：1993-4998
• 卷排序：22

文摘

To solve the problems of noise, detail loss and poor contrast in the successive mean quantization transform (SMQT), a new SMQT algorithm based on Otsu algorithm is proposed. In this algorithm, we integrate the optimal threshold selected by the Otsu algorithm into the SMQT algorithm, then obtain the successive mean quantization of the binary tree. By this algorithm, an enhanced image is output with a higher quality. From both subjective visual effect and objective quality evaluation, the experimental results show that the improved algorithm reduces noise, improves contrast and makes the image details more clear.