Centered Fourier Spectrum Analysis
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Based on the centered Fourier spectrum, Fourier frequency spectrum, and mean value calculations, we can further compute the average value of an image as one of its key features. By calculating the image's mean value, we gain insight into the average brightness or color intensity across all pixels, thereby enhancing our understanding of the image's overall characteristics and content. This process typically involves transforming the image to frequency domain using Fast Fourier Transform (FFT), applying spectrum centering through fftshift operations, and computing statistical measures. The implementation commonly utilizes functions like numpy.fft.fft2() for 2D FFT, numpy.fft.fftshift() for spectrum centering, and numpy.mean() for average value calculation, providing efficient numerical computation for image analysis applications.
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