Abstract: In this paper, we present a new panchromatic sharpening method based on quality parameter optimization. Traditionally, quality metrics such as UIQI, CORR, and ERGAS have been used to assess the quality of panchromatic sharpening. Generally, HPF (high pass filtering) based panchromatic sharpening methods produce good performance. However, one problem with these methods is the peak noise that arises due to a small denominator value when the mean shift problem is addressed. In order to address this problem, we introduce an offset value that was optimized based on a quality metric. We assumed that the offset value was invariant with respect to the spatial scale, and it was used to enhance the resolution of the original multispectral images by using a high-resolution panchromatic image. The experimental results demonstrate that the proposed method showed better performance than some existing panchromatic sharpening methods.
Publication Year: 2010
Publication Date: 2010-08-19
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot