Hyperspectral anomaly detection with nonlocal self-similarity priordoi:10.1117/12.2600404Hyperspectral imageendmember variabilityBayesian unmixinganomaly detectionnonlocal self-similarityIn hyperspectral image, the variation of endmember may significantly alter the signature of corresponding endmember, which influences...
Nonlocal Self-similarityFoveal PerformanceBlur KernelPatch WindowDistance WindowWhen we gaze a scene, our visual acuity is maximal at the fixation point (imaged by the fovea, the central part of the retina) and decreases rapidly towards the periphery of the visual field. This phedoi:10.1007/s11...
( GMM) was developed to learn the nonlocal self-similarity prior.Secondly,based on the Stable Principal Component Pursuit( SPCP) method,the noise image matrix was decomposed into low-rank,sparse and noise parts,while the sparse matrix contained useful information.Finally,the global objective ...
Young-Joo Han and Ha-Jin Yu, "SS-BSN: Attentive Blind-Spot Network for Self-Supervised Denoising with Nonlocal Self-Similarity", IJCAI, 2023. PDF BibTex ArxivAbstractRecently, numerous studies have been conducted on supervised learning-based image denoising methods. However, these methods rely ...
Therefore, we make use of the residual image in method noise to exploit nonlocal self-similarity further. Figure 2 (a) Open in figure viewerPowerPoint NLM denoising performance. (a) Original image; (b) noisy image (σ = 20); (c) initial estimate; (d) method noise; (e) method ...
As an attempt to tackle these flaws, we should explore another widely used image prior well-known as nonlocal self-similarity (NSS) prior. The NSS prior depicts the repetitiveness of higher level patterns (e.g., textures and structures) globally positioned in images. The starting work is the...
Specifically, the GSR model is utilized to simultaneously enforce the intrinsic local sparsity and the nonlocal self-similarity of natural images, while the NLTV model is explored to characterize the smoothness of natural images on a larger scale than the classical total variation (TV) model. To ...
Hyperspectral image (HSI) denoising is a fundamental problem in remote sensing and image processing. Recently, nonlocal low-rank tensor approximation-based denoising methods have attracted much attention due to their advantage of being capable of fully exploiting the nonlocal self-similarity and global...
Nonlocal methods are state-of-the-art in SAR despeckling, thanks to their ability to exploit image self-similarity. Given sufficient training data, however, methods based on deep learning have proven highly competitive. Therefore, to take the best of both approaches, we investigate the use of ...
Toscani, Intermediate asymptotics beyond homo- geneity and self-similarity: long time behavior for ut = ∆φ(u). Arch. Rational Mech. Anal. 180 (2006) 127–149. [9] J. Carrillo, A. Ju¨ngel, P. Markowich, G. Toscani, A. Unterreiter, Entropy dissipation methods for degenerate ...