/DIP_Project

Digital Image Processing Course Project

Primary LanguageMatlab

DIP_Project

Digital Image Processing Course Project

How to use

  • ImageAssessment.fig -> UI file
  • ImageAssessment.m -> UI functions
  • ./func -> functions folder(add to path first)
  • ./src -> resources(include test img)
  • Open application:
    • load image want to be evaluated and original image
    • assess image
    • face detection

UI

References

quick review of the functions.
cite: sharpness metric

  • Mean Squared Error(MSE)
    • the difference between the estimator and what is estimated
  • RMSE
    • represents the sample standard deviation of the differences between predicted values and observed values
  • Signal-to-noise ratio(SNR)
    • compares the level of a desired signal to the level of background noise.
    • In image processing: the ratio of the mean pixel value to the standard deviation of the pixel values over a given neighborhood

SNR

  • PSNR
    • used to measure the quality of reconstruction of lossy compression codecs (e.g., for image compression)
    • The signal in this case is the original data, and the noise is the error introduced by compression
    • When comparing compression codecs, PSNR is an approximation to human perception of reconstruction quality
    • <25 bad quality; 25-35 can see differences; >37 differences can hardly distinguish
  • MS-SNR
    • any meaning?
  • Entropy
    • Entropy is defined as sum(p.*log2(p)) where p contains the histogram counts returned from IMHIST.
    • unit: bits/pixel -> how much info in each pixel

Entropy

  • Normalized Cross-Correlation
    • cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other
  • Average Difference
    • total sum of error divide size of pic
  • Structural Content
    • calc structural similarity
    • The large value of Structural Content (SC) means that image is poor quality.
  • Maximum Difference
    • max value of error in pic
    • The large value of Maximum Difference (MD) means that image is poor quality
  • Laplacian Mean Square Error
    • This measure is based on the importance of edges measurement
    • The large value of Laplacian Mean Square Error (LMSE) means that image is poor quality.
  • Normalized Absolute Error
    • total sum of absolute error divide sum of origin pic value
    • The large value of Normalized Absolute Error(NAE) means that image is poor quality
  • SSIM
    • SSIM is used for measuring the similarity between two images.
    • The SSIM formula is based on three comparison measurements between the samples of x and y: luminance l, contrast c and structure s.
  • Luminance
    • convert rgb2hsv, use mean value of v.(0-1) -> v*255(0-255)
    • bigger value brighter
  • Contrast
    • calc the squared sum of ceter pixel value and four neighbor values, then divide by the number of squared terms
    • bigger value more contrast
  • Sharpness
    • faster than Global Phase Coherence, using Gaussian random field.
    • see paper
    • higher is sharper
  • NIQE
    • calculates the no-reference image quality score for image A using the Naturalness Image Quality Evaluator (NIQE).
    • A smaller score indicates better perceptual quality.
  • Brisque
    • calculates the no-reference image quality score for image A using the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE).
    • A smaller score indicates better perceptual quality.
  • Structural Similarity Index (SSIM)
    • Computation of three terms: luminance, contrast, structural
    • The overall index is a multiplicative combination of the three terms

SSIM

Reference