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This study presents a rapid image completion system comprising a training (or analysis) process and an image completion (or synthesis) process. The proposed system adopts a multiresolution approach, which not only improves the convergence rate of the synthesis process, but also provides the ability to deal with large replaced regions. In the training process, a down-sampling approach is applied to create a patch-based texture eigenspace based on multiresolution background region information. In the image completion process, an up-sampling approach is applied to synthesize the replaced foreground regions. To ensure the continuity of the geometric texture structure between the original background scene regions and the replaced foreground regions, directional and nondirectional image completion approaches are developed to reconstruct the global geometric structure and to enhance the local detailed features of the replaced foreground regions in the lower and higher resolution level images, respectively. Moreover, the synthesis priority order of the individual patches and the appropriate choice of completion scheme (i.e., directional or nondirectional) are both determined in accordance with a Hessian matrix decision value (HMDV) parameter. Finally, a texture refinement process is performed to optimize the resolution of the synthesized result.

Existing tone reproduction schemes are generally based on a single image and are, therefore, unable to accurately recover the local details and colors of scene since the limited available information. Accordingly, the proposed tone reproduction system utilizes two images with different exposures (one low and one high) to capture the local detail and color information of low- and high-luminance regions of scene, respectively. The adaptive local region of each pixel is developed in order to appropriately reveal the details and maintain the overall impression of scene. Our system implements the local tone mapping and color mapping based on the adaptive local region by taking the lowly-exposed image as the basis and referencing the information of highly-exposed image. The local tone mapping compresses the luminance range in the image and enhances the local contrast to reveal the details, while the local color mapping maps the precise color information from the highly-exposed image to the lowly-exposed image. Finally, a fusion process is proposed to mix the local tone mapping and local color mapping results to produce the output image. A multiresolution approach is also developed to reduce time cost. The experimental results confirm that the system generates realistic reproductions of HDR scenes.

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