Curve Fitting Based on Edge Enhancement of Depth Map with Super-resolution Reconstruction

• Main Authors: Chih-Chun Lin, 林治均
• Other Authors: Pei-Jun Lee
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/rwe37w

碩士 === 國立暨南國際大學 === 電機工程學系 === 106 === With the ever-changing technology, the requirements for image quality are gradually increasing. As the DVD evolves into today’s HD and Ultra HD, the demand of high resolution is necessary. High-resolution video or video with high-quality details and rich color content make it important in all fields, such as digital cameras and video cameras, medical imaging, satellite imaging and video surveillance systems are needed to enhance the picture quality. When an image is acquired via an acquisition system, it is usually possible to transform it into a low-resolution image due to imaging conditions, imaging factors, and hardware limitations that can cause the image to be ruined. In addition to the color map information, the enhancement and reconstruction of the depth map information is also the key to improving the image quality and the overall quality of the three-dimensional image. By using the theory of super-resolution reconstruction, the damaged and corrupted images can obtain lost information through the techniques of restoration and reconstruction. The coverage of super-resolution reconstruction theory is very broad. This dissertation discusses and emphasizes on the super-resolution reconstruction of the enhancement at the edge of depth map. The main research topic of this paper is: how to use the polynomial regression of curve fitting to simulate the missing information at the edge of the depth map. At the edge of depth map, polynomial regression is used to reconstruct the lost high frequency information. For the non-edge area, the traditional bicubic interpolation is adopted for reducing compute complexity. Finally, the super-resolution reconstruction architecture is set up to generate high-resolution image sequence. The input is set as multi-frame image sequence. Combining with spatial and temporal information, the traditional interpolation is used at current frame to enhance the resolution and adjacent frame information generated by the residual is utilized to substitute into the corresponding filter to improve the accuracy of super-resolution reconstruction. The experimental results show that the PSNR of the high-resolution video sequence reconstructed by the proposed method is 1 ~ 2 dB about average higher than the traditional bi-cubic interpolation method, and the hit rate at the edge is also about 10 ~ 20% higher, can effectively enhance the visual quality.