Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Sectional non-linear enhancement method for urinary sediment image

A urine sediment, non-linear technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of not meeting real-time requirements, easy to increase noise, etc., achieving fast processing speed, simple calculation, and enhanced target information. Effect

Inactive Publication Date: 2013-01-02
DIRUI MEDICAL TECH CO LTD
View PDF2 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to solve the limitations of the existing image enhancement methods, such as the inability to meet the real-time requirements, easy to increase noise and other problems, and provide a piecewise nonlinear transformation image enhancement method

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
  • Sectional non-linear enhancement method for urinary sediment image
  • Sectional non-linear enhancement method for urinary sediment image
  • Sectional non-linear enhancement method for urinary sediment image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] A method for segmental nonlinear enhancement of a urine sediment image according to the present invention, the specific steps are as follows:

[0032] see figure 1 Shown:

[0033] The first step: According to the distribution range of the cells and the background in the image in the gray space, the genetic algorithm is used to calculate the segmentation points, and the whole image is divided into the background segment, the target segment and the transition segment according to the segment points. According to the pixel gray value distribution of the urine sediment cells and background collected in the statistics, the whole image is divided into the background segment, the target segment and the transition segment, and the gray value of the background distribution is The interval is called the background segment (such as figure 2 shown); count the gray intervals of each cell distribution, the background and the gray intervals of cell distribution overlap and intersec...

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 a sectional non-linear enhancement method for a urinary sediment image. The method comprises the following steps of: a first step: calculating section points by using a genetic algorithm according to distribution ranges of cells in the image and background in a gray space, dividing the whole image into a background section, a target section and a transition section according to the section points, calling a gray-level zone of distributed background as the background section, counting the gray-level zone of each distributed cell, ensuring that the gray-level zones in which the backgrounds and the cells are distributed have overlapped and crossed areas to find out the most proper thresholds to divide the two zones, and selecting a gray-level zone with less than 100 pixels as the transitional section; and a second step: performing different gray-level transformation method on the background section, the target section and the transition section. The method has the beneficial effects that the enhancement method is high in processing speed and stable and reliable; and the noise of the background is well inhibited, and the whole image is obvious in vision effect.

Description

technical field [0001] The invention relates to an image enhancement method, in particular to a segmental nonlinear enhancement method for urine sediment images. Background technique [0002] At present, there are many image enhancement methods, mainly including spatial domain method and frequency domain method. The spatial domain method mainly includes grayscale transformation, histogram equalization, Laplace sharpening, etc.; the frequency domain method mainly includes homomorphic filtering, wavelet transform, etc. The details of these methods are as follows: [0003] (1) Grayscale transformation. Grayscale transformation is to map the grayscale r in the original image f(x, y) to the grayscale s in the enhanced image g(x, y), so that the dynamic range of the image grayscale can be expanded or compressed, thereby enhancing the image contrast . Commonly used grayscale transformations include: linear transformation, piecewise linear transformation and nonlinear transforma...

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 宋洁行长印
Owner DIRUI MEDICAL TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com