Online Low-Light Sand-Dust Video Enhancement Using Adaptive Dynamic Brightness Correction and a Rolling Guidance Filter

Also Available Domains Image Enhancement

Project Code :TMMAIP441

Objective

To enhance low-light sand-dust videos, an adaptive dynamic brightness correction and rolling guidance filter improve contrast, illumination, and noise reduction.

Abstract

Sand-dust videos obtained in a low-light environment are characterized by low contrast, nonuniform illumination, color cast, and considerable noise. To realize sand-dust removal and brightness enhancement simultaneously, this article proposes an online low-light sand-dust video enhancement method using adaptive dynamic brightness correction and a rolling guidance filter. The proposed dual-threshold interframe detection strategy involves two methods to treat low-light sand-dust video frames. The first method involves two components: an adaptive dynamic brightness correction algorithm to correct the color deviation of the low-light video frame and improve its brightness and a rolling guidance filter combined with guided image filtering to enhance the frame details. The second method enhances the quality of the incoming frame by reducing the amount of calculation. The first frame of the video is processed using the first method. The processing method of each subsequent frame is determined according to its interframe detection value with the buffer frame. Through qualitative and quantitative comprehensive experiments on low-light sand-dust images and videos, the performance of the proposed method is compared with those of state-of-the-art methods. The proposed method for frame quality improvement achieves the best visual effect in enhancing the quality of low-light sand-dust images, as indicated by the best objective evaluation indicators. Moreover, compared with the framewise enhancement method, the video processing efficiency associated with the dual threshold interframe detection strategy is 2.77 times higher.

Index Terms—Low-light sand-dust video, adaptive dynamic brightness correction, rolling guidance filter, dual-threshold interframe detection strategy.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software: Matlab 2020a or above

Hardware:

Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016

Processors:

Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support

Disk:

Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space

RAM:

Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

·   Introduction to Matlab

·   What is EISPACK & LINPACK

·   How to start with MATLAB

·   About Matlab language

·   Matlab coding skills

·   About tools & libraries

·   Application Program Interface in Matlab

·   About Matlab desktop

·   How to use Matlab editor to create M-Files

·   Features of Matlab

·   Basics on Matlab

·   What is an Image/pixel?

·   About image formats

·   Introduction to Image Processing

·   How digital image is formed

·   Importing the image via image acquisition tools

·   Analyzing and manipulation of image.

·   Phases of image processing:

               o  Acquisition

               o  Image enhancement

               o  Image restoration

               o   Color image processing

               o  Image compression

               o   Morphological processing

               o   Segmentation etc.,

·   How to extend our work to another real time applications

·   Project development Skills

               o   Problem analyzing skills

               o   Problem solving skills

               o   Creativity and imaginary skills

               o   Programming skills

               o   Deployment

               o   Testing skills

               o   Debugging skills

               o   Project presentation skills

               o   Thesis writing skills

Demo Video