Microlocal analysis of edge flatness through directional multiscale representations

Guo, Kanghui; Labate, Demetrio

doi:10.1007/s10444-016-9486-8

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…Various diseases often occur in children and adults. Magnetic resonance imaging (MRI) is an important imaging tool used to investigate the presence of certain abnormalities in thigh [16], [17]. Because of the nature of quantitative MRI imaging data, this requires a considerable amount of human intervention and expertise training opportunities.…”

Section: Introductionmentioning

confidence: 99%

Comparative studies of multiscale edge detection using different edge detectors for MRI thigh

2021

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Edge detection plays an important role in computer vision to extract object boundary. Multiscale edge detection method provides a variety of image features by different resolution at multiscale of edges. The method extracts coarse and fine structure edges simultaneously in an image. Due to this, the multiscale method enables more reliable edges are detected. Most of the multiscale methods are not translation invariant due to the decimated process. They mostly depend on the corresponding transform coefficients. These methods need more computation and a larger storage space. This study proposes a multiscale method that uses an average filter to smooth image at three different scales. Three different classical edge detectors namely Prewitt, Sobel and Laplacian were used to extract the edges from the smooth images. The edges extracted from the different scales of smooth images were then combined to form the multiscale edge detection. The performances of the multiscale images extracted from the three classical edge detectors were then compared and discussed.

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Section: Introductionmentioning

confidence: 99%