On the other hand, Convolutional Sparse Coding (CSC) has been successfully proved for representing gray-scale images, however it misses any correlation between images. This work considers the spatial-spectral correlation within SIs introducing an extension of the CSC signal model describing the SI as...
We then introduce a novel technique, based on convolutional sparse coding (CSC), and show how it outperforms the state-of-the-art, patch-based approach in terms of flexibility and efficiency, due to the convolutional nature of its filter banks. The key idea for CSC high-speed video ...
Fast Convolutional Sparse Coding in the Dual Domain Convolutional sparse coding (CSC) is an important building block of many computer vision applications ranging from image and video compression to deep learning. We present two contributions to the state of the art in CSC. First, we significantly ...
Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries ...
Convolutional sparse codingConvolutional neural networkAdaptiveThe convolutional sparse coding-based super-resolution (CSC-SR) method has shown its good performance in single image super-resolution. It divides the low-resolution (LR) image into low-frequency part and the high-frequency part, and ...
A pytorch implementation of a ACSC model based onLerned Convolutional Sparse Codingmodel proposedhereand orhere. ACSC block description Evaluation of different ASCS variants ImageLenaHousePepperCoupleFgprBoatHillManBarbara ACSC131.2831.6929.8829.1126.4329.3129.3529.3627.85 ...
python sparsity optimization cuda admm sparse-coding dictionary-learning optimization-algorithms robust-pca fista convolutional-sparse-coding total-variation sparse-representations convolutional-dictionary-learning total-variation-minimization plug-and-play-priors Updated Apr 29, 2024 Python alphacsc / alphacsc...
In**放纵 上传281.53 MB 文件格式 zip clc csc 卷积稀疏编码(Convolutional Sparse Coding)是一种基于信号处理和机器学习的方法,用于对数据进行特征提取和表示学习。它通过将输入信号与一组稀疏滤波器进行卷积操作,从而得到一系列稀疏编码表示。这种方法在处理图像、视频和信号数据时特别有效,能够捕捉数据中的局部特征和...
This paper divides the target into a smooth image and four detail images based on convolutional sparse coding (CSC) and separately establishes target appearance models for them to track targets. The proposed tracker is achieved by combining the tracking results of the two parts to cope with ...
Convolutional neural networks (CNNs) have been tremendously successful in solving imaging inverse problems. To understand their success, an effective strategy is to construct simpler and mathematically more tractable convolutional sparse coding (CSC) models that share essential ingredients with CNNs. Existi...