A sparse filtering method for fast optical imaging data

A technology of optical imaging and sparse filtering, applied in the field of image processing

Active Publication Date: 2019-02-26
SHANDONG UNIV
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  • Abstract
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However, this method is prone to artifacts

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  • A sparse filtering method for fast optical imaging data
  • A sparse filtering method for fast optical imaging data
  • A sparse filtering method for fast optical imaging data

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Embodiment 1

[0083] like Figure 1-2 shown.

[0084] A sparse filtering method for fast optical imaging data, comprising the following steps:

[0085] 1) Preliminary estimate

[0086] 1.1) Image segmentation: the image is divided into several overlapping image blocks, and the size of each image block is k×k;

[0087] 1.2) Collaborative filtering: collaborative filtering includes three sub-processes of image block grouping, three-dimensional sparse transformation, transformation coefficient shrinkage and inverse transformation;

[0088] 1.2.1) Image block grouping: Randomly select an image block, which is recorded as a reference block P; search for multiple similar blocks (search step size is 3 pixels) in the window containing the reference block P and the size is K×K, and set A similar block is defined as a candidate block, and the candidate block and the reference block are arranged as a two-dimensional image block sequence, stacked into a three-dimensional image block; the three-dimen...

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Abstract

The invention relates to a sparse filtering method for fast optical imaging data. The method consists of two steps: initial estimation and final estimation. Each step includes three sub-processes: image partitioning, cooperative filtering and aggregation. In the first step, the weighted absolute distance of the noise image is used to match and group the noise image, then the three-dimensional discrete cosine transform is performed and the transform coefficients are preliminarily estimated by using the hard threshold shrinkage. In the second step, the weighted absolute distance of the preliminarily estimated image is used to match and group the noisy image, and then the discrete cosine transform is used to compute the Wiener shrinkage coefficient by using the preliminarily estimated transform coefficient as the approximation of the real data, and finally the final estimation is made by using the Wiener shrinkage.

Description

technical field [0001] The invention relates to a sparse filtering method for fast optical imaging data, belonging to the technical field of image processing. Background technique [0002] OCT images provide detailed ecological information of biological tissues, which can meet clinical applications such as optical biopsy and histology. The main application areas of OCT technology include the detection of eye diseases and skin diseases, as well as the early detection of cancer in human soft tissues. Ophthalmologists can use OCT technology to image the front and back of the eye to observe and measure the inner layers of the retina corresponding to the anatomical structure. These layer structures are important for the early detection of many ophthalmic diseases such as glaucoma, age-related macular degeneration and diabetes. clinical significance. OCT technology can obtain clear images of tissues based on the spectral characteristics and structures of cancerous tissues that a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T5/008G06T2207/10101G06T2207/20052
Inventor 付树军刘国华王凤苓王红李玉亮林博文付耕
Owner SHANDONG UNIV
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