Digital Signal Processing (DSP) is vital in image processing and computer vision, enhancing and analyzing visual data:
- Image Enhancement: Improves visual quality through contrast enhancement, noise reduction, and sharpening.
- Image Restoration: Corrects distortions or degradations with techniques like Wiener filtering.
- Feature Extraction: Identifies and isolates features for tasks such as object recognition using edge detection and Fourier transforms.
- Compression: Reduces image size without significantly sacrificing quality using algorithms like the Discrete Cosine Transform.
- Morphological Processing: Processes images based on their structure, applying operations like dilation and erosion.
- Segmentation: Divides images into parts for detailed analysis, crucial in medical imaging and autonomous driving.
- Pattern Recognition: Identifies patterns within images for face and gesture recognition using template matching and neural networks.
- 3D Reconstruction: Reconstructs 3D models from 2D images, essential in virtual reality and robotic surgery.
- Motion Analysis: Analyzes motion within image sequences, used in video surveillance and animation.
DSP provides the foundation for processing and transforming images, enabling significant advancements across diverse applications.