This work aims to develop a novel function of the digital camera, i.e., region-filling after object removal from a digital photograph. This problem is defined as how to "guess" the Lacuna region after removal of an object by replicating a part from the remainder of the whole image with visually plausible quality. We propose a hybrid region-filling algorithm composed of a texture synthesis technique and an efficient interpolation method with a refinement approach: 1) the "subpatch texture synthesis technique" can synthesize the Lacuna region with significant accuracy; 2) the "weighted interpolation method" is applied to reduce computaion time; and 3) the "artifact detection mechanism" integrates the Kirsch edge detector and color ratio gradients to detect the artifact blocks in the filled region after the first pass of filling the Lacuna region when the result may not be satisfactory. This can lead to resynthesizing the artifact blocks without user intervention and can be compliant to the unsuccessful results of other algorithms. In the procedure of region-filling, color texture distribution analysis is used to choose whether the subpatch texture synthesis technique or the weighted interpolation method should be applied. In the subpatch texture synthesis technique, the actual pixel values of the Lacuna region are synthesized by adaptively sampling from the source region. The experimental results show that our proposed algorithm can achieve a better performance than previous methods. Particularly, the regular computation of our proposed algorithm is more suitable for implementation of the hardware in a digital camera.

This work aims for a novel function for smart cameraredundant object removal from digital photograph. The proposed novel framework can fill the left lacuna region in the digital image. In previous related researches, texture synthesis and image inpainting construct the fundamentals of filling the lost image region. Texture synthesis can be used to fill the large hole of input texture, while image inpainting can be used to repair the small image gaps. In this paper, we propose an object removal framework by the sub-patch texture synthesis algorithm and weighted interpolation method with automatic repainting mechanism. In the filling process, the color distribution analysis is used to choose different methods. The exhaustive computation time is reduced by the weighted interpolation method. In order to repaint the faulty texture region intelligently, we use the color ratio gradients to detect the synthesized artifact region. The automatic artifact detection can lead repainting the faulty region without user intervention. The proposed algorithm can achieve better performance with seamless output images. The regular computation is also suitable for hardware architecture different from previous existing algorithms.