Multiple exposure integration with image denoising

We propose a denoising technique for multiple exposure image integration. In our method, noise removal is achieved by the wavelet-shrinkage for multiple exposures, and a novel weighting scheme for the integration. A weighted image is converted to the low and the high frequency elements by the shift invariant wavelet transform, and the wavelet coefficient in the high frequencies are decreased by thresholding based on the wavelet-based hard shrinkage. The weight is designed to reduce sensor noise and quantization noise in the process of the multiple exposure integration. Our method works well especially for noise in shadow areas. We show the validity of the proposed algorithm by simulating the method with some actual noisy images.