The analog signal output by the infrared detector is usually sampled as a 14-bit high-dynamic-range digital infrared image, which is not compatible with most 8-bit display systems and cannot be directly used for imaging display. Therefore, image compression quality is very important for image display .This paper studies and analyzes the mapping technology of the base layer, focusing on the traditional limited contrast histogram equalization method (CLAHE). Considering that the conventional CLAHE method is applied to infrared images, there will be a problem of excessive stretching of some uniform areas. a new algorithm for Contrasted Limited Adaptive Histogram Equalization based on uniform region test (M-CLAHE) is proposed. Based on the traditional CLAHE method, this method introduces a gradient operator to extract the contour boundary of the sub-region image, and quantifies the complexity of the image region to solve the above problems. The experimental results show that compared with the traditional CLAHE infrared image compression method, this method can more than double the visual indicators such as image contrast and average gradient compared with the traditional visualization method. This method has engineering portability, and it can be transplanted to the infrared movement to increase the image quality of most scenes by about twice.
High dynamic range (HDR) imaging is an area of increasing importance, but most display devices still have limited dynamic range(LDR). Dynamic range represents the ability of the imaging system to restore the real scene. With the continuous development of imaging systems toward high sensitivity, a higher dynamic range imaging system is more and more demanded. Aiming at the dynamic range expansion problem of the cooled infrared imaging system, this paper proposed a super-framing algorithm to enlarge image dynamic range. Specifically, a model for automatically selecting the integration settings of such images is presented based on the camera characteristic function. It is used to calculate the optimal integration time of different temperature targets in the scene. Afterwards, fuse these frames into an image which possesses all well-exposed areas and give a sense of capturing a high dynamic range scene. Experimental results demonstrate that the system dynamic range can effectively improve 10dB when fusing three frame images. the system dynamic range is from 70dB up to 80dB, the temperature range is from 20°C up to 370°C. The strength of the proposed method lies in its ability to avoid high computational cost using traditional irradiance method applied in the infrared imaging field. Its great performance is conductive to human observation with good imaging effect, low computational complexity and engineering feasibility. The method can be applied to engine test, explosion flame and other high dynamic scenes with high temperature targets.
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