TY - JOUR
T1 - Despeckling of Ultrasound Images Using Block Matching and SVD in Sparse Representation
AU - Reyes-Reyes, Rogelio
AU - Aranda-Bojorges, Gibran H.
AU - Garcia-Salgado, Beatriz P.
AU - Ponomaryov, Volodymyr
AU - Cruz-Ramos, Clara
AU - Sadovnychiy, Sergiy
N1 - Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - This work proposes a novel scheme for speckle suppression on medical images acquired by ultrasound sensors. The proposed method is based on the block matching procedure by using mutual information as a similarity measure in grouping patches in a clustered area, originating a new despeckling method that integrates the statistical properties of an image and its texture for creating 3D groups in the BM3D scheme. For this purpose, the segmentation of ultrasound images is carried out considering superpixels and a variation of the local binary patterns algorithm to improve the performance of the block matching procedure. The 3D groups are modeled in terms of grouped tensors and despekled with singular value decomposition. Moreover, a variant of the bilateral filter is used as a post-processing step to recover and enhance edges’ quality. Experimental results have demonstrated that the designed framework guarantees a good despeckling performance in ultrasound images according to the objective quality criteria commonly used in literature and via visual perception.
AB - This work proposes a novel scheme for speckle suppression on medical images acquired by ultrasound sensors. The proposed method is based on the block matching procedure by using mutual information as a similarity measure in grouping patches in a clustered area, originating a new despeckling method that integrates the statistical properties of an image and its texture for creating 3D groups in the BM3D scheme. For this purpose, the segmentation of ultrasound images is carried out considering superpixels and a variation of the local binary patterns algorithm to improve the performance of the block matching procedure. The 3D groups are modeled in terms of grouped tensors and despekled with singular value decomposition. Moreover, a variant of the bilateral filter is used as a post-processing step to recover and enhance edges’ quality. Experimental results have demonstrated that the designed framework guarantees a good despeckling performance in ultrasound images according to the objective quality criteria commonly used in literature and via visual perception.
KW - block matching
KW - denoising
KW - mutual information
KW - singular value decomposition
KW - speckle
KW - superpixel segmentation
KW - ultrasound image
KW - ultrasound sensors
UR - http://www.scopus.com/inward/record.url?scp=85133514387&partnerID=8YFLogxK
U2 - 10.3390/s22145113
DO - 10.3390/s22145113
M3 - Artículo
C2 - 35890790
AN - SCOPUS:85133514387
SN - 1424-8220
VL - 22
JO - Sensors
JF - Sensors
IS - 14
M1 - 5113
ER -