Comparing RGB to HSI and RGB to YCbCr Histogram Equalized Pictures Using SNR/PSNR Measures

To compare RGB to HSI and RGB to YCbCr histogram equalized pictures using SNR/PSNR measures in C++, you would need to follow these steps:

1. Load and Read Original RGB Image

Load the original RGB image into your C++ program and read its pixel values for further processing.

2. Convert RGB Image to HSI or YCbCr Color Space

Perform color space conversions from RGB to either HSI or YCbCr color space. This step is crucial for further processing and analysis.

3. Perform Histogram Equalization

Apply histogram equalization on the HSI or YCbCr image to enhance the image quality and improve visual appearance.

4. Convert Equalized Image Back to RGB Color Space

Convert the equalized image back to RGB color space for comparison and evaluation purposes.

5. Calculate SNR and PSNR Values

Calculate the Signal-to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR) between the original RGB image and the equalized RGB image. These measures will help quantify the quality of the image processing steps.

6. Compare Results

Repeat the above steps for both RGB to HSI and RGB to YCbCr conversions and compare the SNR and PSNR values obtained. This comparison will indicate the effectiveness of histogram equalization in different color spaces.

Please note that while SNR and PSNR measures are commonly used in image compression evaluation, their application in comparing color space conversions may require additional considerations. Implementing this comparison in C++ would likely involve utilizing image processing libraries like OpenCV for efficient processing.