High Dynamic Range Video Streams Based on Inexpensive Image Sensors

• Main Authors: Sheng-Yi Peng, 彭聖懿
• Other Authors: Pao-Chi Chang
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/14088654831622865599

碩士 === 國立中央大學 === 通訊工程學系在職專班 === 104 === Over the years, the camera is become the part of every person’s life. From the beginning, the traditional film camera first came out, Kodak Instamatic, and then came the digital camera. Now most of the people even don’t carry camera anymore, instead using a smart phone, it can take not bad picture and automatically upload to the cloud, or post to the social network. Smart phone brings us a lot of benefits, and also very convenient. But the flip side of that, it has to be small and easy to be carried, which is limit the pixel size and performance of imaging sensors. This directly affects the dynamic range of the image. When run into a high contrast scene which existed with sun light and the shadows. There are bright and dark details need to be recorded. High Dynamic Range (HDR) processing method is used for solving this kind of problems. So far, it already has lots of kind of HDR techniques, like Exposure Fusion. Recently there are many related research. It has the better image quality, and less the artifact, but the higher computational complexity. And there is the traditional HDR Tone Mapping method. It has the lower computational complexity, but easy to caused the halo artifact. This thesis is focused on the Tone Mapping technique. We can use the highly efficiency HDR processing method on the low cost CMOS image sensor, do the real time display. And take into account the work flow of the back-end Image Sensor Processor (ISP). Let the HDR image flow and normal LDR image flow can use the same parameter, such as Auto White Balance (AWB), Color Correction Matrix (CCM) and Gamma Correction, etc. With new hardware architecture, it can provide two different exposures in the same frame. New hardware is also much reduced the time interval between two exposure images, so the ghosting effect will less occurred. Then, we improve the existing HDR processing technique; consider the video streaming instead of static imaging. We used a pixel based Global Tone Mapping method to deal with the video streaming, and a highly computational complexity Local Tone Mapping method for the static images (snap shot), which can provide better image quality. So the photographer can take control the light and shooting angle more easily by viewing the real time HDR video streaming.