G21-2025-Final Project

import numpy as np

import matplotlib.pyplot as plt

def generate_individual_graphs():

    # Input gradient (0 to 1)

    x = np.linspace(0, 1, 500)

    # The three specified Gamma values

    gamma_values = [0.5, 3, 50]

    for gamma in gamma_values:

        plt.figure(figsize=(8, 6))

        # 1. Reference Line (Linear - No Correction)

        # This is the 'Reference Curve'. It shows the output without blending/correction.

        plt.plot(x, x, 'k--', label='Linear Reference (No Correction)', alpha=0.5)

        # 2. Gamma Correction Curve

        # Logic: y = x^(1/gamma)

        y = np.power(x, 1.0 / gamma)

        # Plotting the curve

        plt.plot(x, y, color='blue', linewidth=3, label=f'Gamma Correction (γ={gamma})')

        # Decoration

        plt.title(f'Gamma Correction Curve: γ = {gamma}', fontsize=14)

        plt.xlabel('Input Pixel Intensity (0 to 1)', fontsize=12)

        plt.ylabel('Corrected Output Intensity', fontsize=12)

        plt.legend(loc='best')

        plt.grid(True, alpha=0.3)

        plt.xlim(0, 1.0)

        plt.ylim(0, 1.05)

        # Saving separate files for each gamma

        filename = f"gamma_curve_{gamma}.png"

        plt.savefig(filename)

        print(f"Generated graph: {filename}")

        # Close plot to start fresh for next gamma

        plt.close()

if __name__ == "__main__":

    generate_individual_graphs()