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Every analytic function in the registry is normalized to f(z) = z + a₂z² + a₃z³ + …. The lab turns that single coefficient sequence aₙ into an image operator and applies it to a photo, so you can see - not just prove - what each function's geometry does: its coefficients become a directional convolution kernel (sharpen / smooth / edge), or the function itself is used as a conformal warp w = f(z) of the image disk. For each run you get the visual output, a distortion map versus the original, the coefficient sequence, the kernel's frequency response, and standard full-reference image-quality metrics (PSNR, SSIM - Wang 2004, GMSD - Xue 2014). The subordinating entries are the Ma–Minda φ-functions from Prof. Asha's program (cardioid, sine, nephroid-type, exp-cardioid, quartic) - the same classes whose coefficient bounds are certified on the Proofs page.
Function
Application
Gain 3.0
Kernel
Test image:
Original
Visual output
Distortion map (|out − orig|, jet)
Frequency response (DC center)
Coefficient seq. aₙ (blue + / red −)
Kernel matrix
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