anandr07 / Improving-Quality-of-Low-Light-Images

This project focuses on improving the image quality of low-light images using a deep learning-based approach. The implemented solution involves the use of a convolutional neural network (CNN) to enhance the details and visual appeal of images captured in challenging lighting conditions.

Image Quality Enhancement for Low-Light Images

Overview

This project focuses on improving the image quality of low-light images using a deep learning-based approach. The implemented solution involves the use of a convolutional neural network (CNN) to enhance the details and visual appeal of images captured in challenging lighting conditions.

Requirements

• Python 3.x
• Libraries: NumPy, Pandas, OpenCV, Matplotlib, Keras

Usage

Clone the repository:

```bash
git clone https://github.com/anandr07/Improving-Quality-of-Low-Light-Images
```

Model Architecture

The image enhancement model is based on a custom-designed convolutional neural network. The architecture includes multiple convolutional layers, skip connections, and final convolutional layers to produce the enhanced image.

Example Output

The final section of the script visualizes the results by displaying the ground truth, low-light image, and the enhanced image side by side.

Image Filters:

Original Image:

Black and White Image:

Custom Filters: