空域 Resources

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2. Image Enhancement: Image enhancement, also known as image sharpening, aims to strengthen detail information such as contour edges in images. Similar to image smoothing, image enhancement can be performed in both spatial and frequency domains. For spatial domain sharpening: subtracting the original image from a processed version yields the sharpened image g(i,j), i.e., g(i,j) = f(i,j) - α[f(i+1,j) + f(i-1,j) + f(i,j+1) + f(i,j-1) - 4f(i,j)] = f(i,j) + 4α[f(i,j) - avg]. Here α is an adjustable factor controlling sharpening intensity, where 1/4 represents the average gray value of the 4 neighboring points around the sharpened pixel.

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Implementation in Spatial Domain The core principle of LSB digital watermarking: Modifying the least significant bit of binary images doesn't affect visual perception. Based on this, watermark information can directly replace the least significant bits of digital images. The embedding process consists of three main steps: 1. Convert spatial domain pixel values from decimal to binary representation using bit-level operations 2. Replace the least significant bits of corresponding data with each bit of binary watermark information through bit manipulation 3. Convert the watermarked binary data back to decimal pixel values to obtain the watermarked image using appropriate conversion functions

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This source code implements an image restoration approach using sparse prior, featuring comparisons between frequency-domain and spatial-domain restoration techniques. The implementation includes referenced research on "Deconvolution using natural image priors" and demonstrates practical parameter optimization strategies.

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