INTRESTED IN IDEA: Computational photography algorithms for better image quality
Amaresh Koti
Hi OpenCV GSoC Team,
I hope everyone is doing well. I am Amaresh, and I am thrilled at the prospect of working on the "Improving Image Quality" project for GSoC 2025. Upon going through the project description, I believe this is an excellent opportunity to stretch the limits of what OpenCV can achieve with respect to image quality enhancements. I'm actually very dedicated to producing quality work and have been thinking about how to approach this challenge.
**Project Vision and Approach**
I'd prefer to divide the project into smaller, more manageable tasks so that we can tackle each sector effectively. Here's a snapshot of my plan:
- **Advanced Denoising Algorithms:**
I'm going to explore both conventional denoising methods and more recent approaches, such as deep learning and adaptive filtering. My aim is to eliminate noise without compromising the image details as sharp and natural.
- **Vignetting Correction:**
For this, I’d develop a method to estimate the vignette effect from sample images and then reverse it using a correction function. I’m considering a mix of model-based approaches and machine learning to handle various conditions.
- **Chromatic Aberration Correction:**
I plan to work on color channel alignment by quantifying the misalignment of the color channels. Methods such as edge-based matching and iterative optimization can be used to correct these chromatic aberrations efficiently.
- **Improved White Balance and Exposure Correction:**
My strategy here will be to produce algorithms that parse image histograms and correct white balance according to scene properties. Exposures could be corrected through local contrast expansion and tone mapping to produce better-balanced, more natural results.
- **Multi-Frame Denoising and Superresolution:**
With the help of multiple images, I seek to minimize noise and increase resolution through frame alignment and fusion. I'm working with both traditional algorithms and current optimization methods to create a reliable processing pipeline.
- **Deblurring and Color Enhancement:**
I’d also like to dive into deblurring techniques, such as blind deconvolution, to restore clarity in images. In tandem, enhancing colors and reducing the effects of fog should help bring out the vibrancy without altering the true essence of the scene.
**Why I’m Fully Committed**
I'm really interested in pushing the frontiers of image processing and computer vision. My experience in algorithm design and software development—combined with practical use of OpenCV—leads me to believe that I can make a valuable contribution to this project. I'm looking forward to delivering real-world solutions to the opencv_photo module or the opencv_contrib repository, along with tests and examples that will be useful to the community at large.
I'd appreciate the chance to further brainstorm my ideas and collaborate to tweak the scope of the project to fit what is needed by the community. Thanks for reviewing my application. I hope to hear from you and hopefully be a part of OpenCV's success going forward.
Sincerely,
K. Amaresh
amaresh...@gmail.com
[LinkedIn Profile](https://www.linkedin.com/in/amaresh-koti-270347285/)