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Based on improved l 0 Image smoothing method and system for gradient minimization model

An image smoothing and minimization technology, applied in the field of image processing, can solve the problems of losing salient features and unsatisfactory processing effects, etc., and achieve the effect of good salient edge features and good image smoothing effect

Active Publication Date: 2022-07-26
SHANDONG UNIV OF FINANCE & ECONOMICS
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the application of the first-order gradient information, after processing the color image, the block-by-block smooth areas are obtained, and the color of each smooth area is the same, and local salient features are lost, resulting in poor processing effects for some applications such as object recognition. ideal

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  • Based on improved l <sub>0</sub> Image smoothing method and system for gradient minimization model
  • Based on improved l <sub>0</sub> Image smoothing method and system for gradient minimization model
  • Based on improved l <sub>0</sub> Image smoothing method and system for gradient minimization model

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Embodiment 1

[0034] This embodiment provides an improved L-based 0 Image smoothing method for gradient minimization model;

[0035] like figure 1 shown, based on the improved L 0 Image smoothing methods for gradient minimization models, including:

[0036] Obtain the image to be smoothed; input the image to be smoothed into the improved L 0 In the gradient minimization model; output the smoothed image;

[0037] The improved L 0 Gradient minimization model, including: 0 norm combined with the first regularization term of the Laplacian operator, and the L 0 The second regularization term combined with the Sobel operator;

[0038] The Laplacian operator is used to constrain the color change of the image, slow down the change of the image color gradient, and achieve a smooth transition of the image color; the Sobel operator is used to maintain the edge features of the image and reduce the loss of image detail features.

[0039] Further, the Laplacian operator is a second-order gradient...

Embodiment 2

[0086] This embodiment provides an improved L-based 0 Image smoothing system for gradient minimization models;

[0087] Based on improved L 0 Image smoothing systems for gradient minimization models, including:

[0088] an acquisition module, which is configured to: acquire the image to be smoothed;

[0089] The input module is configured to: input the image to be smoothed into the improved L 0 In the gradient minimization model;

[0090] an output module, which is configured to: output the smoothed image;

[0091] The improved L 0 Gradient minimization model, including: 0 norm combined with the first regularization term of the Laplacian operator, and the L 0 The second regularization term combining the norm and the Sobel operator;

[0092] The Laplacian operator is used to constrain the color change of the image, slow down the change of the image color gradient, and achieve a smooth transition of the image color; the Sobel operator is used to maintain the edge feature...

Embodiment 3

[0097] This embodiment also provides an electronic device, comprising: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are Stored in the memory, when the electronic device runs, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in the first embodiment.

[0098] It should be understood that, in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic devices , discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

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Abstract

The present invention discloses an improved L-based 0 An image smoothing method and system for a gradient minimization model, comprising: acquiring an image to be smoothed; inputting the image to be smoothed into an improved L 0 Gradient minimization model; output smoothed image; the improved L 0 Gradient minimization model, including: 0 norm combined with the first regularization term of the Laplacian operator, and the L 0 The second regularization term combining the norm and the Sobel operator; the Laplacian operator is used to constrain the color change of the image, slow down the change of the color gradient of the image, and realize the smooth transition of the image color; use the Sobel operator to realize the edge of the image The preservation of features reduces the loss of image detail features.

Description

technical field [0001] This application relates to the technical field of image processing, especially to the improved L 0 Image smoothing method and system for gradient minimization models. Background technique [0002] The statements in this section merely mention the background art related to the present application and do not necessarily constitute prior art. [0003] Edge-preserving smoothness of images, that is, maintaining the smoothness of image edge features, is a basic problem in computer vision research. Its goal is to preserve the salient edges of the image in the process of smoothing the image. Image edge-preserving smoothing has many applications in image processing. It is not only the basis of image denoising, image enhancement, and non-realistic image rendering, but also can be used as preprocessing for other applications. [0004] Common traditional methods of image edge preservation and smoothing include local methods based on filtering and global method...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/20192
Inventor 高珊珊李孟航张丽倩
Owner SHANDONG UNIV OF FINANCE & ECONOMICS
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