Local binary pattern (LBP) is a classical descriptor used to extract the local spatial texture features of images, which has been widely applied to image feature description and matching. However, the existing LBP algorithms for HSI are based on the single-dimensional description, which leads to the limitations on the expression of spatial ...

Dec 1, 2024 · To tackle these issues, we develop a novel local binary pattern named LatLBP for investigating spatial-spectral latent information, which provides a low-dimensional, fine-grained, high-level representation of dual-domain latent semantic information by exploring the group structure of data.

Jul 22, 2020 · Local Binary Patterns are used to characterize the texture and pattern of an image/object in an image. However, unlike Haralick texture features, LBPs process pixels locally which leads to a more robust, powerful texture descriptor.

In this paper, we address this problem and show that multi-dimensional LBP histograms pro-vide effective texture descriptors. We demonstrate, on various texture datasets from the Outex suite and both for texture classification and texture retrieval scenarios, that our proposed approach consistently outperforms conventional LBP features.

Jun 28, 2019 · Local binary pattern (LBP) is a simple but powerful descriptor for spatial features, which can lessen the workload of CNNs and improve the classification accuracy.

In this paper, a classification paradigm to exploit rich texture information of HSI is proposed. The proposed framework employs local binary patterns (LBPs) to extract local image features, such as edges, corners, and spots.

Jan 24, 2017 · Abstract: The local binary pattern (LBP) is a simple and efficient texture descriptor for image processing. Recently, LBP has been introduced for feature extraction of hyperspectral imagery.

Abstract: This paper focuses on the Local Binary Patterns and its various important variants. LBP is a non-parametric descriptor and used to extract, analyze, recognize and classify the different modality images. It summarizes the local patterns of image characteristics efficiently.

Jul 6, 2017 · Local binary patterns (LBPs) have been extensively used to yield spatial features for the classification of general imagery, and a few recent works have applied these patterns to the classification of hyperspectral imagery.

Feb 26, 2025 · Hyperspectral images (HSIs) contain rich spectral and spatial information, motivating the development of a novel circulant singular spectrum analysis (CiSSA) and multiscale local ternary...