Color Correction Based on CFA and Enhancement Based on Retinex with Dense Pixels for Underwater Images

Project Code :TMMAIP69


This paper presents a novel color correction method based on color filter array (CFA) and an enhancement method based on Retinex with dense pixels and adaptive linear histogram transformation for degraded color-biased underwater images.


The main theme of this project is to Enhance and Color Correction for underwater images. This project becomes challenging due to attenuation and scattering of light. In this process, the novel colour correction method based on Color Filter Array (CFA) and an enhancement method based on retinex with dense pixels and adaptive linear histogram transformation for degraded colour-biased underwater images. 

For any digital images, which are captured by digital camera with CFA in the RGB space, their RGB values are dependent and coupled because of the interpolation process. So, we try to compensate red channel attenuation of underwater degraded images from the green channel and blue channel. Retinex model has been widely used to efficiently handle low brightness and blurred images. 

The McCann Retinex (MR) method selects a spiral path for pixel comparison to estimate illumination. However, the simple path selection doesn’t include global light dark relationship of the whole image. So, we design a scheme to gain much well-distributed and denser pixels to obtain more precise intensity of illumination. Besides, we design a piecewise linear function for histogram transform, which is adaptive to the whole RGB value.


Keywords: Underwater image enhancement, underwater image color correction, color filter array (CFA), Retinex, McCann Retinex, adaptive histogram transform.

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

Block Diagram


Software Requirements:

MATLAB R2018a or above

Hardware Requirements:

Operating Systems:

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


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.


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


Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

  • Introduction to Matlab
  • 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:
    • Acquisition
    • Image enhancement
    • Image restoration
    • Color image processing
    • Image compression
    • Morphological processing
    • Segmentation etc.,
  • How to enhance and correct the color of image using Image Processing
  • How to extend our work to another real time applications
  • Project development Skills:
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

Demo Video

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