【摘要】：隨著顯示技術(shù)的不斷更新,HDR顯示設(shè)備開(kāi)始進(jìn)行推廣,對(duì)于HDR資源特別是動(dòng)態(tài)的高動(dòng)態(tài)范圍(High Dynamic Range,HDR)資源的需求也越來(lái)越大,如何高效便捷的獲得HDR圖像資源正日益成為一個(gè)研究的熱點(diǎn),并仍然是一個(gè)研究的難點(diǎn)。為了在進(jìn)行圖像捕獲時(shí)更好地構(gòu)建HDR圖像以及將現(xiàn)有低動(dòng)態(tài)范圍(Low Dynamic Range,LDR)圖像轉(zhuǎn)換為HDR圖像,本文首先提出了一種基于光源采樣的單曝光HDR圖像生成算法。該算法基于人眼視覺(jué)系統(tǒng)(Human Visual System,HVS)模型,分別提取出LDR圖像的亮度分量和色度分量。對(duì)LDR圖像的亮度分量進(jìn)行反色調(diào)映射。然后再對(duì)反色調(diào)映射后圖像的高光區(qū)域進(jìn)行采樣,將采樣結(jié)果作為圖像中的光源進(jìn)行擴(kuò)展。在擴(kuò)展過(guò)程中為模擬光線(xiàn)散射效應(yīng)及盡可能地保持該區(qū)域的細(xì)節(jié),進(jìn)行高斯濾波和腐蝕操作。最后,在色度分量與亮度分量的圖像融合過(guò)程中,對(duì)圖像進(jìn)行調(diào)整,進(jìn)一步拉伸圖像暗區(qū)域的對(duì)比度,并對(duì)暗區(qū)域噪聲起到一定程度的抑制作用。實(shí)驗(yàn)表明,該算法能通過(guò)單曝光LDR圖像生成HDR圖像,處理效果較好,能滿(mǎn)足實(shí)時(shí)性要求。而針對(duì)單曝光LDR圖像細(xì)節(jié)信息不足的問(wèn)題,本文還提出了一種基于細(xì)節(jié)層分離的單曝光HDR圖像生成算法。該算法結(jié)合HVS模型,將LDR圖像分離出亮度分量和色度分量。對(duì)分離出來(lái)的亮度分量進(jìn)行伽馬校正,之后再對(duì)伽馬校正后的圖像采用濾波操作,進(jìn)行細(xì)節(jié)層分離。然后將分離出來(lái)的細(xì)節(jié)層與亮度分量分別進(jìn)行反色調(diào)映射后進(jìn)行融合得到新的亮度分量。最后將各圖像分量融合得到最終的HDR圖像。實(shí)驗(yàn)表明該算法能挖掘出部分隱藏的圖像細(xì)節(jié)信息,處理效果較好,能滿(mǎn)足實(shí)時(shí)性要求,具有較好的魯棒性。
[Abstract]:With the continuous updating of display technology, HDR display equipment has been popularized, and the demand for HDR resources, especially for dynamic high dynamic range (High Dynamic Range,HDR) resources, is also increasing. How to obtain HDR image resource efficiently and conveniently is becoming a hot research topic, and it is still a difficult point. In order to better construct HDR images and convert the existing low dynamic range (Low Dynamic Range,LDR images to HDR images, a single exposure HDR image generation algorithm based on light source sampling is proposed in this paper. Based on the human visual system (Human Visual System,HVS) model, the algorithm extracts the luminance component and chroma component of LDR image respectively. The brightness component of LDR image is inversely mapped. Then, the high-light region of the image is sampled, and the sampling result is extended as the light source in the image. In order to simulate the light scattering effect and keep the detail of the region as much as possible, Gao Si filter and corrosion operation are carried out during the expansion process. Finally, in the process of image fusion of chrominance component and luminance component, the image is adjusted to further stretch the contrast of the dark area of the image, and the noise of the dark area is suppressed to a certain extent. Experiments show that the algorithm can generate HDR image by single exposure LDR image, and the processing effect is good, which can meet the requirement of real time. In order to solve the problem of lack of detail information in single exposure LDR image, a single exposure HDR image generation algorithm based on detail layer separation is proposed in this paper. Combined with HVS model, the algorithm separates the luminance component from the chroma component of the LDR image. Gamma correction is performed on the separated luminance component, and then filtering operation is used to separate the detail layer of the image after gamma correction. Then the separated detail layer and the luminance component are mapped inversely and fused to obtain the new luminance component. Finally, the final HDR image is obtained by fusion of each image component. Experimental results show that the proposed algorithm can mine some hidden image details, have better processing effect, meet the real-time requirements, and have better robustness.
【學(xué)位授予單位】：西南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.41

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本文編號(hào)：2425917