OpenCL-based parallel optimization method of image de-noising algorithm

An optimization method and image technology, applied in image enhancement, image data processing, calculation, etc., can solve the problems of image denoising algorithm with large computational load, reduced processing time, and long running time.

Active Publication Date: 2015-10-21
XIDIAN UNIV
View PDF5 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the large amount of calculation and long running time of the image denoising algorithm, it cannot meet the real-time pro...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • OpenCL-based parallel optimization method of image de-noising algorithm
  • OpenCL-based parallel optimization method of image de-noising algorithm
  • OpenCL-based parallel optimization method of image de-noising algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0051] see Figure 1~3 , in the embodiment of the present invention, a parallel optimization method of an OpenCL-based image denoising algorithm uses 3 kernels on the GPU, kernel_xxstep is mainly responsible for using the joint bilateral filter to obtain the base layer of the image, and kernel_wls is mainly responsible for using the joint WLS to obtain Image base layer, kernel_fft is mainly responsible for detail layer acquisition, detail layer denoising and image addition us...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an openCL-based parallel optimization method of an image de-noising algorithm. According to an idea of image layering, an image is divided into a high-contrast base layer and a low-contrast detail layer by using a combined dual-side filtering algorithm and a combined WLS algorithm; de-noising processing is carried out on the detail layer by using stockham FF; and then image restoring is carried out by changing frequency spectrum contraction and image adding methods, thereby realizing the de-noising effect. According to the invention, on the basis of characteristics of large execution function processing data volume and high data parallelism of the base layer obtaining and detail layer de-noising processing, the openCL platform model is used and parallel calculation of the image de-noising algorithm is realized on GPU; and then details of the calculation process are modified, wherein the modification processing contains local internal memory usage, proper working team size selection, and parallel reduction usage and the like. The speed-up ratio of the de-noising algorithm that is realized finally can reach over 30 times; and thus the practicability of the algorithm can be substantially improved.

Description

technical field [0001] The invention relates to the field of parallel computing and the technical field of image processing algorithms, in particular to a parallel optimization method of an OpenCL-based image denoising algorithm. Background technique [0002] As an important carrier for human beings to feel and transmit information, images play a very important role in people's lives, especially with the continuous development of computer technology, computer vision and image processing technology are getting deeper and deeper into all aspects of social life, such as Medical care, intelligent monitoring, etc. However, noises are inevitably introduced at various stages of image and video generation, transmission, and processing, such as Gaussian noise generated by sensitive components, Poisson noise generated by photoelectric conversion, and various noises in the transmission process. The noise in the image seriously affects the visual effect of the image and brings great in...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T5/00
Inventor 沈沛意张向东宋娟张亮朱光明
Owner XIDIAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap