{"id":20187,"date":"2020-09-27T14:16:00","date_gmt":"2020-09-27T08:46:00","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/histogram-equalization-explained\/"},"modified":"2024-04-30T17:01:44","modified_gmt":"2024-04-30T11:31:44","slug":"histogram-equalization-explained","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/histogram-equalization-explained\/","title":{"rendered":"What is Histogram Equalization and how it works?"},"content":{"rendered":"\n
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  1. Introduction<\/a><\/strong><\/li>\n\n\n\n
  2. Histogram equalization<\/a><\/strong><\/li>\n\n\n\n
  3. Steps Involved <\/a><\/strong><\/li>\n\n\n\n
  4. Algorithm<\/a><\/strong><\/li>\n\n\n\n
  5. Example<\/a><\/strong><\/li>\n\n\n\n
  6. CLAHE (Contrast Limited Adaptive Histogram Equalization)<\/a><\/strong><\/li>\n<\/ol>\n\n\n\n

    Contributed by: Sreekanth<\/a> <\/em><\/strong><\/p>\n\n\n\n

    Introduction to Histogram Equalization<\/strong><\/h2>\n\n\n\n

    Image pre-processing<\/a> is the term for operations on the images at the lowest level of abstraction. These operations do not increase image information content, but they decrease it if entropy is an information measure. The aim of pre-processing is an improvement of the image data that suppresses undesired distortions or enhances some image features relevant for further processing and analysis tasks.  <\/p>\n\n\n\n

    There are four different types of Image Pre-Processing techniques, and they are listed below.<\/p>\n\n\n\n

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    1. Pixel brightness transformations\/ Brightness corrections<\/li>\n\n\n\n
    2. Geometric Transformations<\/li>\n\n\n\n
    3. Image Filtering and Segmentation <\/li>\n\n\n\n
    4. Fourier transform and Image restoration<\/li>\n<\/ol>\n\n\n\n

      Histogram equalization is one of the Pixel brightness transformations techniques. It is a well-known contrast enhancement technique due to its performance on almost all types of image. <\/p>\n\n\n\n

      Also Read: What is Image Recognition and how is it used? <\/a><\/p>\n\n\n\n

      Histogram equalization<\/strong><\/h2>\n\n\n\n

      A histogram is a representation of frequency distribution. It is the basis for numerous spatial domain processing techniques. Histogram manipulation can be used for image enhancement. <\/p>\n\n\n\n

      Contrast is defined as the difference in intensity between two objects in an image. If the contrast is too low, it is impossible to distinguish between two objects, and they are seen as a single object. <\/p>\n\n\n\n

      Histogram equalization is a widely used contrast-enhancement technique in image processing because of its high e\ufb03ciency and simplicity. It is one of the sophisticated methods for modifying the dynamic range and contrast of an image by altering that image such that its intensity histogram has the desired shape. It can be classified into two branches as per the transformation function is used.<\/p>\n\n\n\n