Estimating Radiometric Response Functions from Image Noise Variance
نویسندگان
چکیده
We propose a method for estimating radiometric response functions from observation of image noise variance, not profile of its distribution. The relationship between radiance intensity and noise variance is affine, but due to the non-linearity of response functions, this affinity is not maintained in the observation domain. We use the nonaffinity relationship between the observed intensity and noise variance to estimate radiometric response functions. In addition, we theoretically derive how the response function alters the intensity-variance relationship. Since our method uses noise variance as input, it is fundamentally robust against noise. Unlike prior approaches, our method does not require images taken with different and known exposures. Real-world experiments demonstrate the effectiveness of our method.
منابع مشابه
A Radiometric Noise Model for Estimating Geometrical Parameters of 3-D Bodies from Multispectral Images
Camera images can be used to measure the geometry of man-made objects. An iterative weighted least-squares estimator with knowledge of imaging and reflection models retrieves the geometrical parameters of objects in a 3-D scene from 2-D image projections. We investigate the use of multispectral imagery which allows us to separate diffuse and specular reflection before estimating geometry. We bu...
متن کاملRadiometric framework for image mosaicking.
Nonuniform exposures often affect imaging systems, e.g., owing to vignetting. Moreover, the sensor's radiometric response may be nonlinear. These characteristics hinder photometric measurements. They are particularly annoying in image mosaicking, in which images are stitched to enhance the field of view. Mosaics suffer from seams stemming from radiometric inconsistencies between raw images. Pri...
متن کاملRobust single image noise estimation from approximate local statistics
A novel method for estimating the variance and standard deviation of the additive white Gaussian noise contained in an image will be presented. Only a single image is used to estimate the noise properties. Local image outliers are discarded, this allows us to separate the additive zero mean white Gaussian noise contained in a noisy image from the original image structure. Local variance estimat...
متن کاملComparative Analysis of Image Denoising Methods Based on Wavelet Transform and Threshold Functions
There are many unavoidable noise interferences in image acquisition and transmission. To make it better for subsequent processing, the noise in the image should be removed in advance. There are many kinds of image noises, mainly including salt and pepper noise and Gaussian noise. This paper focuses on the research of the Gaussian noise removal. It introduces many wavelet threshold denoising alg...
متن کاملAn automatic method for estimating noise-induced signal variance in magnitude-reconstructed magnetic resonance images
Signal intensity in magnetic resonance images (MRIs) is affected by random noise. Assessing noise-induced signal variance is important for controlling image quality. Knowledge of signal variance is required for correctly computing the chi-square value, a measure of goodness of fit, when fitting signal data to estimate quantitative parameters such as T1 and T2 relaxation times or diffusion tenso...
متن کامل