Display and Compute Grayscale Histograms for Images with Advanced Processing Capabilities

This system computes and visualizes grayscale histograms for images, supporting both grayscale and RGB image formats through color space conversion algorithms. The implementation includes adaptive brightness and contrast adjustment using gamma correction and histogram stretching techniques. Advanced image processing operations such as edge detection (utilizing Sobel, Canny, or Prewitt operators) and image filtering (including Gaussian, median, and bilateral filters) are integrated through modular function calls. These processing capabilities enable comprehensive image analysis and editing, producing optimized visual outcomes. Additionally, geometric transformations like image cropping with coordinate validation and rotation using affine transformations are available. The system also supports annotation features including text overlay with font rendering and vector graphic drawing operations, providing users with flexible image customization tools. Overall, this functionality expands image processing options through a method-driven architecture, enabling diverse image manipulation and modification approaches. Key implementation details: - RGB-to-grayscale conversion uses weighted luminance calculation (0.299R + 0.587G + 0.114B) - Histogram computation employs binning algorithms with configurable range optimization - Contrast adjustment implements piecewise linear transformation with clipping prevention - Edge detection kernels are applied through 2D convolution with boundary handling - Filter operations utilize separable kernel implementations for computational efficiency