Integrated noise modeling for image sensor using bayer domain images

  • Baek, Yeul-Min
  • Kim, Joong-Geun
  • Cho, Dong-Chan
  • Lee, Jin-Aeon
  • Kim, Whoi Yul
Citations

SCOPUS

5

초록

Most of image processing algorithms assume that an image has an additive white Gaussian noise (AWGN). However, since the real noise is not AWGN, such algorithms are not effective with real images acquired by image sensors for digital camera. In this paper, we present an integrated noise model for image sensors that can handle shot noise, dark-current noise and fixedpattern noise together. In addition, unlike most noise modeling methods, parameters for the model do not need to be re-configured depending on input images once it is made. Thus the proposed noise model is best suitable for various imaging devices. We introduce two applications of our noise model: edge detection and noise reduction in image sensors. The experimental results show how effective our noise model is for both applications.

키워드

Additive White Gaussian noiseFixed pattern noiseImage processing algorithmImaging deviceInput imageIntegrated noise modelsNoise modelingNoise modelsNoise reductionsReal imagesAdditive noiseCamerasDigital image storageGaussian noise (electronic)Image processingImage sensorsNoise abatementWhite noiseEdge detection
제목
Integrated noise modeling for image sensor using bayer domain images
저자
Baek, Yeul-MinKim, Joong-GeunCho, Dong-ChanLee, Jin-AeonKim, Whoi Yul
DOI
10.1007/978-3-642-01811-4_37
발행일
2009-05
유형
Conference Paper
저널명
Lecture Notes in Computer Science
5496 LNCS
페이지
413 ~ 424