Joon Hyuk Cha

Seamless and Fast Panoramic Image Stitching

In this paper, a novel panoramic imaging method is presented which can compensate tone differences between images precisely by estimating ghost pixels in the overlap area. The method compensates the overlapped images bilaterally, then it prevents a panoramic image from getting darker or lighter as images are stitched. Therefore, the proposed method allows the overall panorama to keep the proper mid-tone, offering a high-speed panorama system with only software implementation in spite of its outstanding performance. Experimental results show that the proposed method can correct 95% serious corner cases taking less time than existing methods.

A simple ghost-free exposure fusion for embedded HDR imaging

We propose a simple ghost-free exposure fusion algorithm in which three (over-, mid-, under-) exposures are input for fast embedded HDR imaging. Previous methods in this area require a complicated post-processing, such as morphological operations and large size kernel operations. To remove ghost artifacts successfully even with a low computing power, first of all an over-exposure input is set as a reference image, and non-ghostness probability is applied to acquire a ghost-free fusion weight. Through some experimental analysis, we show that such a reference image setting scheme makes it possible to skip the heavily time consuming post-processing.

Stereo panoramic image stitching with a single camera

In this paper, we present stereo panoramic imaging method which generates stereo panoramas by stitching sequential images captured from a single camera under a hand-held sweeping condition. It is hard to take sequential images without a shake under a hand-held sweeping condition. The tilt of the camera makes the rotation of input images which causes the misaligned stereo panoramas. The misaligned stereo panoramas make the degradation of the stereo perception and the dizziness of the viewers. In order to make well-aligned stereo panoramas, we propose the vertical local alignment of the left and right strips using a reference panorama. The proposed method is measured against the existing method about in terms of disparity ranges.