A Study on Impulse Noise Reduction Using CNN Learned by Divided Images
Yasushi Amari, Takashi Miyazaki, Yusuke Koshimura, Yasuki Yokoyama, Hiroaki Yamamoto · 2018
Random noise, which is one of impulse noise, and fixed pattern noise are known to be generated during imaging in a CMOS image sensor. In recent years, fixed pattern noise has been decreased due to the improvement of a CMOS image sensor performance. However, the random noise generated by photon fluctuation in the process of photon detection using photodiode still remains as a problem. So far, many denoising methods have been proposed to remove the random noise in images. In addition, we have already proposed one of denoising methods. However, our method requires an approximate threshold to obtain superior image quality. In this paper, we propose a method to effectively remove the noise superimposed on digital images using Deep Learning, which attracts attention in the field of image recognition and is applied in various fields. In addition, we report results that we compared our method with other conventional denoising methods.