Discuss the types of redundancies in images with examples

Mumbai University > Computer Engineering > Sem 7 > Image Processing

Marks: 10 Marks

Year: Dec 2015


Redundancy can be broadly classified into Statistical redundancy and psych visual redundancy.

  • Statistical redundancy can be classified into inter-pixel redundancy and coding redundancy.
  • Inter-pixel can be further classified into Spatial redundancy and Temporal redundancy.
  • Spatial redundancy or correlation between neighboring pixel values.
  • Spectral redundancy or correlation between different color planes or spectral bands.
  • Temporal redundancy or correlation between adjacent frames in a sequence of images in video applications.
  • Image compression research aims at reducing the number of bits needed to represent an image by removing the spatial and spectral redundancies as much as possible.
  • In digital image compression, three basic data redundancies can be identified and exploited: Coding redundancy, Inter-pixel redundancy and Psych visual redundancy.

  • Coding Redundancy:

    • Coding redundancy is associated with the representation of information.
    • The information is represented in the form of codes.
    • If the gray level of an image is coded in a way that uses more code symbols than absolutely necessary to represent each gray level then the resulting image is said to contain coding redundancy.
  • Inter-pixel Spatial Redundancy:

    • Interpixel redundancy is due to the correlation between the neighboring pixels in an image.
    • That means neighboring pixels are not statically independent. The gray levels are not equally probable.
    • The value of any given pixel can be predicated from the value of its neighbors that is they are highly correlated.
    • The information carried by individual pixel is relatively small. To reduce the interpixel redundancy the difference between adjacent pixels can be used to represent an image.
  • Inter-pixel Temporal Redundancy:

    • Interpixel temporal redundancy is the statistical correlation between pixels from successive frames in video sequence.
    • Temporal redundancy is also called interframe redundancy. Temporal redundancy can be exploited using motion compensated predictive coding.
    • Removing a large amount of redundancy leads to efficient video compression.
  • Psychovisual Redundancy:

    • The Psychovisual redundancies exist because human perception does not involve quantitative analysis of every pixel or luminance value in the image.
    • It’s elimination is real visual information is possible only because the information itself is not essential for normal visual processing.
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