標題: | Image Contrast Enhancement Using Classified Virtual Exposure Image Fusion |
作者: | Lee, Chang-Hsing Chen, Ling-Hwei Wang, Wei-Kang 資訊工程學系 Department of Computer Science |
關鍵字: | Classified virtual exposure image fusion;contrast enhancement;exposure fusion;image fusion |
公開日期: | 1-十一月-2012 |
摘要: | In our daily life, digital cameras and smart phones have been widely used to take pictures. However, digital cameras and smart phones have a limited dynamic range, which is much lower than that human eyes can perceive. Thus, the photographs taken in high dynamic range scenes often exhibit under-exposure or over-exposure artifacts in shadow or highlight regions. In this study, an image fusion based approach, called classified virtual exposure image fusion (CVEIF), is proposed for image enhancement. First, a function imitating the F-stop concept in photography is designed to generate several virtual images having different intensity. Then, a classified image fusion method, which blends pixels in distinct luminance classes using different fusion functions, is proposed to produce a fused image in which every image region is well exposed. Experimental results on four different kinds of generic images, including a normal image, a low-contrast images, a backlight image, and a dark scene image, have shown that the proposed CVEIF approach produced more pleasingly enhanced images than other methods(1). |
URI: | http://dx.doi.org/10.1109/TCE.2012.6414993 http://hdl.handle.net/11536/21097 |
ISSN: | 0098-3063 |
DOI: | 10.1109/TCE.2012.6414993 |
期刊: | IEEE TRANSACTIONS ON CONSUMER ELECTRONICS |
Volume: | 58 |
Issue: | 4 |
起始頁: | 1253 |
結束頁: | 1261 |
顯示於類別: | 期刊論文 |