Handwritten MATLAB Code for Image FFT and DCT Transformations

In this article, I present my custom MATLAB implementations for FFT (Fast Fourier Transform) and DCT (Discrete Cosine Transform) operations specifically designed for handwritten image processing. These codes enable comprehensive frequency domain analysis, which constitutes a crucial aspect of digital image processing. The implementation includes optimized algorithms for efficient transformation of spatial domain images to frequency domain representations, allowing users to extract meaningful frequency components and analyze image characteristics. Through frequency domain analysis, we can gain deeper insights into image features and structural patterns. My code provides practical tools for understanding and processing handwritten images, featuring functions that handle image preprocessing, transformation computations, and result visualization. The FFT implementation uses radix-2 algorithm for efficient computation, while the DCT code employs type-II transformation suitable for image compression applications. These implementations serve as valuable resources for researchers and developers working on advanced image analysis and pattern recognition projects involving handwritten content.