Calculating Normalized Mean Square Error Between Recovered and Original Images Through Programming
Through computational programming, the normalized mean square error between the restored image and the original image is determined as:
Horizontal Localization of License Plates Using Horizontal and Vertical Projection Images
Achieving horizontal positioning of license plates through analysis of horizontal and vertical projection images from original input, implementing projection-based boundary detection algorithms for accurate license plate region identification.
Removal of Horizontal Stripes from Images
This technique effectively restores original image quality by eliminating horizontal stripe artifacts using specialized image processing algorithms
Partitioning Original Images into e x e Pixel Blocks for Fractal Analysis
Divide the original image into e x e pixel sub-blocks, identify maximum and minimum values in each block, calculate and quantize their differences, then compute fractal values using r x r sub-blocks with texture analysis implementation
Fourier Phase Spectrum of Images
Experimental Content: (1) Compute frequency responses of three given templates and visualize their 3D surface plots; select an image and perform convolution operations using each template, comparing processed images with the original to analyze template types and the differences/connections between templates (b) and (c). (2) Select an image, apply Discrete Fourier Transform (DFT), reconstruct the image using only phase spectrum, then reconstruct using only magnitude spectrum, comparing results; select two distinct image types, perform Fourier transforms, swap their phase spectra, compute inverse Fourier transforms, and compare outcomes to demonstrate the critical role of Fourier phase spectrum in image reconstruction.
Performing DFT and DCT Transformations on an Image with MATLAB
Implementation of Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) on images using MATLAB, with comparative analysis of image reconstruction using only 20 DCT coefficients versus the original image.
Fourier Reconstruction
Recovering original images using Fourier reconstruction methodology with frequency domain analysis.