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CN-120707422-B - 3D noise reduction method based on guided filtering

CN120707422BCN 120707422 BCN120707422 BCN 120707422BCN-120707422-B

Abstract

The invention discloses a 3D noise reduction method based on guided filtering, which relates to the technical field of digital image processing and comprises the steps of utilizing motion estimation to match each pixel point of an input frame to obtain a corresponding pixel point in a reference frame, respectively extracting an image block of a R, G, B channel based on each pixel point to serve as a target image block, extracting a corresponding guided image block in the reference frame to match, and utilizing guided filtering to conduct filtering processing on the target image block and the guided image block in the reference frame to obtain a noise-reduced output image block. The invention can achieve high-quality noise reduction effect, reduce image distortion caused by non-translational motion, is easy to realize by hardware, and is convenient to realize with low cost.

Inventors

  • JI BEICHEN
  • WANG BIN
  • Qiao Bensen

Assignees

  • 江苏稻源科技集团有限公司

Dates

Publication Date
20260508
Application Date
20250616

Claims (6)

  1. 1. A guided filtering based 3D noise reduction method, comprising: matching each pixel point of the input frame by utilizing motion estimation to obtain a corresponding pixel point in the reference frame; Based on each pixel point, respectively extracting an image block of the R, G, B channels as a target image block, and extracting a corresponding guide image block in a reference frame for matching; Filtering the target image block and the guide image block in the reference frame by using guide filtering to obtain a noise-reduced output image block; Filtering the target image block and the guide image block in the reference frame by using guide filtering, and obtaining the noise-reduced output image block comprises the following steps: calculating coefficients in the guided filter linear model according to the relation between the guided image block and the target image block; calculating the pixel value of the central point of the output image block based on the obtained coefficient, and calculating the output pixel value of R, G, B channels of each pixel point; in the filtering process, the contribution of different guide image blocks is balanced by using the idea of non-local mean value and setting weights; Traversing all pixel points in the image, respectively carrying out filtering treatment on a target image block and a guide image block, and finally generating a complete output image block after noise reduction; In the filtering process, by utilizing the non-local mean idea, the step of setting weights to balance the contributions of different guide image blocks comprises the following steps: The multi-guide image block is adopted to replace a single guide image block, and the translation similarity in the image is utilized to improve the noise reduction effect of the smooth area; the contribution of different guiding image blocks is balanced by setting a weight function, and the noise reduction effect is improved by combining the structural similarity and pixel value similarity of the image blocks; based on the limitation of calculation resources, the weight function is replaced by a monotonically decreasing function, and the weight calculation is optimized in a lookup table mode.
  2. 2. The guided filtering-based 3D noise reduction method according to claim 1, wherein the matching each pixel point of the input frame with motion estimation to obtain a corresponding pixel point in the reference frame includes: Taking a current image frame to be noise reduced as an input frame, and taking the image with noise reduction completed as a reference frame; Selecting the pixel points with the same positions in the reference frame as the center of each pixel point of the input frame, and defining a preset matching range of the reference frame; Selecting a preset image block as a matching block by taking a pixel point in an input frame as a center, searching in a preset matching range of a reference frame, and finding out a plurality of similar reference blocks; Calculating the distance between the image block in the reference frame and the matching block in the input frame, comparing the obtained distance with a preset threshold value, and reserving the image block with the distance smaller than the threshold value; and obtaining a matching block corresponding to each pixel point of the input frame in the reference frame through the motion estimation and matching process.
  3. 3. The guided filtering based 3D noise reduction method according to claim 2, wherein the formula for calculating the distance between the image block in the reference frame and the matching block in the input frame is: ; Wherein d represents the distance between the image block in the reference frame and the matching block in the input frame, I represents the matching block, I (I, j, c) represents the pixel value of the matching block in the input frame at coordinates (I, j, c); (i, j, c) represents the pixel value of the image block in the reference frame at coordinates (i, j, c), and m represents the side length of the image block.
  4. 4. The guided filtering based 3D noise reduction method according to claim 1, wherein extracting, on a per pixel basis, an image block of a R, G, B channel as a target image block, and extracting a corresponding guided image block in a reference frame for matching includes: For each pixel point, respectively extracting an image block of the pixel point in R, G, B channels to serve as a target image block; in the reference frame, extracting the position matched with the target image block, extracting the guide image blocks of R, G, B channels respectively, and ensuring that the sizes of the extracted target image block and the guide image block are the same.
  5. 5. The guided filtering based 3D noise reduction method according to claim 1, wherein the formula for calculating coefficients in the guided filtering linear model is: ; Wherein a and b each represent a coefficient; Representing a boot image block; Pixel values representing pixel points of coordinates (I, j) in the guide image block; I r denotes a target image block; representing the pixel value of a pixel point of coordinates (i, j) in a target image block, s representing the distance from a center point to the edge of the image block, epsilon representing a regularization parameter limiting the size of a, m representing the side length of the image block, n representing the matching range; representing the weights.
  6. 6. The guided filtering based 3D noise reduction method according to claim 1, wherein the formula for calculating the pixel value of the center point of the output image block is: ; in the formula, A pixel value representing a center point of the output image block; a and b each represent a coefficient; Representing the weight; representing a boot image block.

Description

3D noise reduction method based on guided filtering Technical Field The invention relates to the technical field of digital image processing, in particular to a 3D noise reduction method based on guided filtering. Background Digital image acquisition is a process of converting optical signals into electric signals by using a sensor such as a camera and the like and storing, transmitting and displaying the electric signals in a digital form, and digital image processing is a process of processing and optimizing an acquired digital image aiming at a using purpose and a scene, wherein common methods comprise image enhancement and restoration, image coding compression, image description and the like. Noise reduction of an image is a very important item of content in image enhancement and restoration. The method is widely applied to various fields such as vehicle-mounted images, monitoring cameras and the like. In some low-illumination environments, such as outdoors in the evening and night, the camera can generate a large number of noise points due to insufficient sensitization, so that in order to display clarity, the low-illumination images need to be noise-reduced, and the real-time information can be acquired clearly by naked eyes conveniently and the clear images can be stored conveniently for subsequent use. The 3D noise reduction technology is an important technology in the field of image processing. It exploits the correlation of image sequences in the time domain to reduce noise. And detecting a corresponding pixel block between two frames through motion estimation, and then performing time domain fusion on the matched pixel block, so that the influence of noise on image quality is reduced by utilizing the randomness of noise statistics. The current mainstream 3D noise reduction method mainly adopts an average or weighted average method during time domain fusion, but for some non-translational motion objects, problems such as blurring and smear can occur in simple average, and the image quality is affected to a certain extent. Guided filtering is an important image processing filtering technique. The key principle is that the information of the guiding image is utilized to carry out filtering processing on the target image. It calculates the filtered output of the target image by defining a local linear model on the guide image. The filtering mode has the edge maintaining characteristic, and can well keep image edge and detail information while removing noise and smoothing images. The local linearity ensures that the local basic structure of the image is unchanged, and the dislocation of the image structure caused by the problems of non-translational motion and the like can be avoided, so that the image distortion is caused. Nowadays, image processing plays an increasingly important role in various fields of intelligent automobiles, intelligent home furnishings, intelligent monitoring and the like, and also puts forward higher requirements on image quality, and a new and more effective 3D noise reduction time domain fusion method has practical value. For the problems in the related art, no effective solution has been proposed at present. Disclosure of Invention Aiming at the problems in the related art, the invention provides a 3D noise reduction method based on guided filtering, which aims to overcome the technical problems existing in the prior related art. For this purpose, the invention adopts the following specific technical scheme: a guided filtering based 3D noise reduction method, comprising: matching each pixel point of the input frame by utilizing motion estimation to obtain a corresponding pixel point in the reference frame; Based on each pixel point, respectively extracting an image block of the R, G, B channels as a target image block, and extracting a corresponding guide image block in a reference frame for matching; And filtering the target image block and the guide image block in the reference frame by using guide filtering to obtain a noise-reduced output image block. Further, matching each pixel point of the input frame by using motion estimation, and obtaining a corresponding pixel point in the reference frame includes: Taking a current image frame to be noise reduced as an input frame, and taking the image with noise reduction completed as a reference frame; Selecting the pixel points with the same positions in the reference frame as the center of each pixel point of the input frame, and defining a preset matching range of the reference frame; Selecting a preset image block as a matching block by taking a pixel point in an input frame as a center, searching in a preset matching range of a reference frame, and finding out a plurality of similar reference blocks; Calculating the distance between the image block in the reference frame and the matching block in the input frame, comparing the obtained distance with a preset threshold value, and reserving the image block with the distance