We present a denoising method based on wavelets and generalized cross validation and apply these methods to image denoising. We describe the method of modified wavelet reconstruction and show that the related shrinkage parameter vector can be chosen without prior knowledge of the noise variance by using the method of generalized cross validation. By doing so, we obtain an estimate of the shrinkage parameter vector and, hence, the image, which is very close to the best achievable mean-squared error result--that given by complete knowledge of the underlying clean image.
This paper presents a rear obstacle detection system by using a single rear view camera. The system can detect various static and moving obstacles behind the cars. An efficient hierarchical detecting strategy is used to achieve high detection rate and low false positives. The temporal Inverse perspective mapping difference image based coarse detection is used to estimate whether there are obstacles in the predetermined warning area at first stage. Then a novel integral image based segmentation algorithm is developed for fine obstacle segmentation. Finally, the blob analysis is utilized for obstacle representation and verification. Our system achieves 94.2% detection rate and 16% false positives rate on 125 challenging video sequences. The average processing speed of the system is 25fps on a standard laptop.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.