R: Compute risks characterizing the quality of smoothing results

risk-methods {aws} | R Documentation

## Compute risks characterizing the quality of smoothing results

### Description

Methods function `risk` in package aws. For an given array `u` the following statistics are computed : Root Mean Squared Error `RMSE <- sqrt(mean((y-u)^2))`, Signal to Noise Ratio `SNR <- 10*log(mean(u^2)/MSE,10)`, Peak Signal to Noise Ratio `PSNR <- 10*log(max(u^2)/MSE,10)`, Mean Absolute Error `MAE <- mean(abs(y-u))`, Maximal Absolute Error `MaxAE <- max(abs(y-u))`, Universal Image Quality Index (UIQI) (Wang and Bovik (2002)).

### Usage

      ## S4 method for signature 'array'
    risk(y, u=0)
      ## S4 method for signature 'aws'
    risk(y, u=0)
      ## S4 method for signature 'awssegment'
    risk(y, u=0)
      ## S4 method for signature 'ICIsmooth'
    risk(y, u=0)
      ## S4 method for signature 'kernsm'
    risk(y, u=0)
      ## S4 method for signature 'numeric'
    risk(y, u=0)

### Arguments

`y` | object
`u` | array of dimension `dim(y)` or `dim(extract(y,what="yhat")$y)` or scalar value used in comparisons.

### Methods

`signature(y = "ANY")`

  The method extract and/or compute specified statistics from object of class

`signature(y = "array")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

`signature(y = "aws")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

`signature(y = "awssegment")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

`signature(y = "ICIsmooth")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

`signature(y = "kernsm")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

`signature(y = "numeric")`

  Returns a list with components `RMSE, SNR, PSNR, MAE, MaxAE, UIQI`

### Author(s)

Joerg Polzehl polzehl@wias-berlin.de

### References

V. Katkovnik, K. Egiazarian and J. Astola, Local Approximation Techniques in Signal And Image Processing, SPIE Society of Photo-Optical Instrumentation Engin., 2006, PM157

Z. Wang and A. C. Bovik, A universal image quality index, IEEE Signal Processing Letters, vol. 9, N3, pp. 81-84, 2002.

[Package aws version 2.5-1 Index]