Application of Infrared Images of Objects with Extreme Temperature Difference for the Structural Elucidation of Drug Molecules

作者：Ding, Dehong; Fang, Kui^*; He, Ming; Yu, Hexiang; Qian, Kejun; Liu, Bo

来源：Latin American Journal of Pharmacy, 2014, 33(10): 1684-1689.

• Chemical imaging
• Drug molecules
• Extreme temperature difference
• Histogram equalization
• Infrared image
• Self-adaptive dual-local area enhancement

Infrared imaging technology of objects has been widely used to elucidate the structure of drug molecules. When observing objects, especially objects with extreme temperature difference, infrared focal plane imaging systems often have difficulties in evenly describing the grayscales of different temperature sections and capturing enough details. Aimed at this problem, in this study we proposed a self-adaptive dual-local area enhancement algorithm. This paper details the algorithm from two aspects, spatial distribution and statistical grayscale characteristics. Based on the spatial distribution of infrared images, this method divides an infrared image into multiple sub-images in a self-adaptive fashion and performs local histogram statistics individually. After analyzing the local spatial grayscale distribution features, self-adaptive sectional equalization is performed to the histogram of each local space. The enhanced local area images are then assembled using linear interpolation, thereby completing the self-adaptive spatial and grayscale local area enhancement of an infrared image. Experimental validation was performed to the algorithm; by applying the algorithm in infrared focal plane imaging system, excellent enhancing results were obtained and the imaging quality was improved significantly, thereby validated the feasibility of the proposed algorithm.

• 出版日期2014
• 单位湖南农业大学; 中国人民解放军信息工程大学