This project demonstrates key concepts of Digital Signal Processing (DSP) through hands-on image processing in both the spatial domain and the frequency domain. It integrates classical DSP techniques with creative image transformations to highlight the practical power of convolution, Fourier analysis, and digital filters.
- Convolution-based Filtering
- Blurring
- Sharpening
- Edge Enhancement
- Noise Processing
- Noise addition
- Noise removal (denoising via spatial & frequency filters)
- Frequency-Domain Filtering
- Band-pass filtering for texture analysis
- Image Compression using Discrete Cosine Transform (DCT)
- Steganography via frequency-domain embedding
- Grayscale filter
- Vignette effect
- Negative filter
- Cyberpunk filter
- Night filter
- Food filter
- Brightness
- Contrast
- Color balance
- Sharpness
All image outputs are reconstructed based on core DSP principles:
- Convolution for spatial filtering
- Fourier Transforms for frequency-domain analysis
- Digital Filters for noise reduction and enhancement