Image Normalization Processing
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The article mentions that we can take certain measures to further improve image processing results. First, we can employ image normalization techniques to achieve better balance in brightness, contrast, and color saturation. This typically involves pixel value transformation using algorithms like Min-Max scaling (x' = (x - min)/(max - min)) or Z-score normalization, often implemented through OpenCV functions such as cv2.normalize(). Second, we can consider implementing digital watermark embedding operations, which enhance copyright protection and anti-piracy capabilities through techniques like Discrete Wavelet Transform (DWT) or Least Significant Bit (LSB) substitution algorithms. These operations provide additional options for improving and safeguarding image quality and integrity through programmable image processing pipelines.
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