Low-light images are seriously corrupted by noise due to the low signal-to-noise ratio. In low
intensity, just-noticeable-difference (JND) is high, and thus the noise is not perceived well by …

Inshore ship detection from very high resolution (VHR) optical remote sensing images has
been playing a critical role in various civil and military applications. However, it brings up an …

Under extreme low-lighting conditions, images have low contrast, low brightness, and high
noise. In this paper, we propose a principal component analysis framework to enhance low …

For the image restoration problem, recent variational approaches exploiting nonlocal
information of an image have demonstrated significant improvements compared with …

Classification is an important pattern recognition paradigm with a multitude of applications in
popular research problems. Utilizing multiple data representations to improve the accuracy …

针对非均匀低照度图像增强问题, 提出了一种动态双稳随机共振算法. 该算法基于双稳态随机
共振模型, 将图像中的噪声能量转移到低照度区域, 能有效对低照度图像进行亮度增强 …

To solve the problem of non-uniform low illuminantion color image enhancement, a dynamic
bistable stochastic resonance (DBSR) algorithm is proposed. Based on the bistable …

Image enhancement (IE) is a common thing we use to get better results from previous
imagery. This image enhancement is not only used by us, but it is implemented in many …

In this paper, an iterative model of self-synaptic FitzHugh-Nagumo (FHN) neurons based on
adaptive stochastic resonance (ASR) and improved by Euler-Maruyamas method is …

In this article, we propose a novel group-based sparse representation (GSR) model for
restoring color images in the presence of multiplicative noise. This model consists of a …