ECE Seminar with Xiaodan Jin

Analysis and Processing of Pixel Binning for Color Image Sensor With Xiaodan Jin University of Dayton Faculty Host: Janusz Konrad Refreshments will be served outside Room 339 at 9:45 a.m. Abstract: Pixel binning refers to the concept of combining the electrical charges of neighboring pixels together to form a superpixel. The main benefit of this technique is that the combined charges would overcome the read noise at the sacrifice of spatial resolution. Binning in color image sensors results in superpixel Bayer pattern data and subsequent demosaicking yields the final, lower resolution, less noisy image. It is common knowledge among the practitioners and camera manufacturers, however, that binning introduces severe artifacts. The in-depth analysis in this article proves that these artifacts are far worse than the ones stemming from loss of resolution or demosaicking, and therefore it cannot be eliminated simply by increasing the sensor resolution. By accurately characterizing the sensor data that has been binned, we propose a post-capture binning data processing solution that succeeds in suppressing noise and preserving image details. We verify experimentally that the proposed method outperforms the existing alternatives by a substantial margin. About the Speaker: Xiaodan Jin received a B.E. in Electronic Science and Technology from Southwest Jiaotong University in 2007 and M.S. in Electrical and Computer Engineering from the University of Dayton in 2010. He is a Research Engineer at the University of Dayton, also a Fellow at the School of Engineering and Applied Sciences, Harvard University. His main research interests include image processing focus on digital camera pipeline processing (denoising, demosaicking, anti-aliasing and white balance, etc.), high dynamic range (HDR) imaging and statistical signal processing.