Prior knowledge of the noise present in a color acquisition device is very important for the recovery of spectral reflectance of an object being imaged, since recovery performance is greatly influenced by the noise.
In the previous paper (IEEE Trans. Image Process. 1848 (2006), the author proposed a new model to estimate noise variance of an image acquisition system by assuming the noise variance in each channel is equal and showed this model is very useful to accurately recover a reflectance of an imaged object. This paper describes extended model for the estimation of the covariance matrix the noise present in an image acquisition system without assumption. It is demonstrated that the proposal overfits noise covariance matrix to learning samples and that recovery performance for the test samples is poor with the previous model. However this overfitting means the estimates are correctly performed using the model. The new model is effective in analyzing the present in an image acquisition system.
You may also like:
- Spectral Image Prediction of Color Halftone Prints Based on Neugebauer Modified Spectral Reflection Image Model
- RAW Image Files: The Way to HDR Image From a Single Exposure
- Spatial and Spectral Analysis and Modeling of Transversal Chromatic Aberrations and Their Compensation
- Fast Non-Iterative PCA Computation for Spectral Image Analysis Using GPU
- Reflectance recovery using localised weighted method