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This limitation motivates the task of hyperspectral unmixing (HU), which seeks to identify the spectral signatures (\n                    <jats:italic>endmembers<\/jats:italic>\n                    ) of the materials present in an observed scene, along with their relative proportions (\n                    <jats:italic>fractional abundance<\/jats:italic>\n                    ) in each pixel. A major challenge in HU arises from class variability among materials, which undermines accurate representation using a single spectral signature, as assumed in the conventional linear mixing model. To address this issue, we propose using group sparsity after representing each material with a set of spectral signatures, known as endmember bundles, where each group corresponds to a specific material. In particular, we develop a bundle-based framework that can enforce either inter-group sparsity or sparsity within and across groups (SWAG) on the abundance coefficients. Furthermore, our framework offers the flexibility to incorporate a variety of sparsity-promoting penalties, among which the transformed\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$\\ell _1$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:msub>\n                            <mml:mi>\u2113<\/mml:mi>\n                            <mml:mn>1<\/mml:mn>\n                          <\/mml:msub>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    (TL1) penalty is a novel regularization in the HU literature. Extensive experiments conducted on both synthetic and real hyperspectral data demonstrate the effectiveness and superiority of the proposed approaches.\n                  <\/jats:p>","DOI":"10.1007\/s10851-026-01295-9","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T12:51:14Z","timestamp":1776430274000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A General Framework for Group Sparsity in Hyperspectral Unmixing Using Endmember Bundles"],"prefix":"10.1007","volume":"68","author":[{"given":"Gokul","family":"Bhusal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifei","family":"Lou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristina","family":"Garcia-Cardona","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ekaterina","family":"Merkurjev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,17]]},"reference":[{"key":"1295_CR1","doi-asserted-by":"publisher","first-page":"S5","DOI":"10.1016\/j.rse.2007.12.014","volume":"113","author":"AFH Goetz","year":"2009","unstructured":"Goetz, A.F.H.: Three decades of hyperspectral remote sensing of the earth: a personal view. 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