A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image

Abstract

An Intensified Charge-Coupled Device (ICCD) image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a) Different from the independent identically distributed (i.i.d.) noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b) The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.

A Denoising Method for Randomly Clustered Noise in ICCD Sensing Images Based on Hypergraph Cut and Down Sampling

“…However, it cannot well eliminate the sparse noise in the image. Thus, rather than fixing the parameter value, we adaptively adjusted it according to the histogram variance of oriented gradient (HVOG) value [ 2 ] of each group. In this way, it can keep the structure information and eliminate the noise well.…”

“…In this way, the ICCD sensor could capture images in low-light environment. An introduction of a real ICCD image sensor was given in [ 2 ].…”

“…It can be seen that the ICCD image induces unexpected structure information and its pattern appears random, which consequently destroys the true structure information of the image. A deep analysis of the random clustered noise has been given in [ 2 ], by comparing it with that of natural images. Indeed, this problem exists not only in ICCD images, but also in other possible scenarios, such as images captured in front of a frosted window.…”

“…In this paper, we focus on removing the randomly clustered noise in ICCD sensing images, which are captured by the ICCD sensor [ 2 ]. The noise removal problem has been well studied for i.i.d.…”

“…Thus, they may not be suitable for the randomly clustered noise in ICCD images. In [ 2 ], we studied this problem based on sparse representation. However, it often loses some textural information of the ICCD image in the smoothing process.…”