| Summary: | 碩士 === 國立中正大學 === 電機工程研究所 === 101 === This thesis investigates the role of non-linear response function (CRF) and uses the defocused blur image of edge features to estimate the camera response unction. We propose a way to render a high dynamic range image by down-sampling the original image. Defocus blur in the process of image capture is an important clue of the camera response function. Because this function contains the haracteristics of non-linear changes, and the real scene changes in the radiation intensity is linear, by comparing the images of defocus blur region intensity variation and real change in the brightness of the scene, we can derivative the camera's response function. With this technology can capture a single image, compare the original and the compressed image data, or the use of multiple images capture, curve fitting the blur region, then obtain the camera response function. In recent years, many researches have been focused on expanding Low Dynamic Range (LDR) images to High Dynamic Range (HDR) images. HDR images contain a broader range of physical values that can be perceived by the human visual system. There are researchers proposed new algorithm to LDR expansion methods, those that are based on the inversion of Tone Mapping Operators (TMOs). Now the image capture device resolution of the photographs is great, most people will not go to print such a high resolution photo. The goal of this thesis is to provide a method to reshape image resolution to extend its dynamic range, then expand to HDR field.
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