Image Pre-processing

Image Pre-processing a Pre-Processing task performed in Computer Vision and involves preparing the acquired images for analysis. It may include procedures such as noise reduction, image enhancement, and normalization to ensure the images are in a suitable format for subsequent processing.

Image Pre-processing tasks:

  • Noise Reduction: Applying filters or algorithms to remove unwanted noise or disturbances from the image, ensuring a cleaner and more accurate representation.
  • Image Enhancement: Adjusting the image's contrast, brightness, or sharpness to improve overall visual quality or highlight specific features.
  • Normalization: Bringing the image data to a standard scale or range, which can be particularly crucial for various machine learning algorithms to ensure uniform processing.
  • Color Conversion: Converting images into different color spaces (e.g., RGB to grayscale, HSV, or YCbCr) to simplify analysis or extract specific information based on color.
  • Image Registration: Aligning multiple images or compensating for any movement or distortion to synchronize them for further processing.
  • Image Segmentation: Dividing the image into meaningful regions or segments to focus on specific areas or objects of interest.
    • It's the process of partitioning a digital image into multiple segments or regions, with the goal of simplifying the image analysis process. This can be done manually, semi-automatically, or fully automatically.