Apply hyperanalytic shearlet transform to geometric separation

Abstract

This paper first proposes a novel image separation method based on the hyperanalytic shearlet. By combining the advantages of both the hyperanalytic wavelet transform and the shear operation, hyperanalytic shearlet is easy to implement and also has a low redundancy. By using such transform and the orthonormal wavelet, a new geometric separation dictionary is obtained which can sparsely represent points and curviline singularities, respectively. In order to get the different components of image faster and more accurate, a fast alternating direction method (FADM) is used to train the dictionary. Our algorithm can greatly improve the computational efficiency without causing damage to the accuracy of image separation. Furthermore, a proper measure to evaluate the separation performance called sep-degree is defined. The experimental results have demonstrated the proposed method's effectiveness and superiority.

SAR Image De-noising Based on Generalized Non-local Means in Non-subsample Shearlet Domain

“…Shearlet is both a more flexible theoretical tool for the geometric representation of images and more natural for implementation. What is more, the Shearlet approach can be associated to a multi-resolution analysis and the Shearlet transform also has highly directional sensitivity, spatially localized and well localized [10,11]. So, we use non-subsample Shearlet in [10] to suppress the speckle in this paper.…”

PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network

“…Danger may appear anywhere at any time; therefore, first responders must monitor a large area continuously in order to identify potential danger and take actions. Due to the dynamic and complex nature of natural disaster, some victims may not be found with a single type of sensor modality; for example, image sensors can be used to spot the victims based on optical images; UWB radar sensors can be applied to penetrate the ground or sense-through-wall [4,5], and acoustic sensors are needed to collect the voice from victims [6]. Overall, image sensors play important roles in HSN.…”