Texture-based measurement of spatial frequency response using the dead leaves target: extensions, and application to real camera systems

Conventional point spread function (PSF) measurement methods often use parametric models for the estimation of the PSF. This limits the shape of the PSF to a specific form provided by the model. However, there are unconventional imaging systems like multispectral cameras with optical bandpass filters, which produce an ab-normal, e.g., unsymmetric PSF. To estimate such PSFs we have developed a new measurement method utilizing a random noise test target with markers: After acquisition of this target, a synthetic prototype of the test target is geometrically transformed to match the acquired image with respect to its geometric alignment. This allows us to estimate the PSF by direct comparison between prototype and image. The noise target allows us to evaluate all frequencies due to the approximately “white” spectrum of the test target we are not limited to a specifically shaped PSF. The registration of the prototype pattern gives us the opportunity to take the specific spectrum into account and not just a “white” spectrum, which might be a weak assumption in small image regions. Based on the PSF measurement, we perform a deconvolution.We present comprehensive results for the PSF estimation results using our multispectral camera andprovide deconvolution results. Best Paper Digital Photography Conference Texture-Based Measurement of Spatial Frequency Response using the Dead Leaves Target: Extensions and Application to Real Camera Systems J. S. McElvain,1 S. P. Campbell,1 E. Jin,2 and J. Miller1; 1Digital Imaging Systems and 2Aptina LLC (USA) Abstract: The dead leaves model was recently introduced as a method for measuring the spatial frequency response (SFR) of camera systems. The target consists of a series of overlapping opaque circles with a uniform gray level distribution and radii distributed as r-3. Unlike the traditional knife-edge target, the SFR derived from the dead leaves target will be penalized for systems that employ aggressive noise reduction. Initial studies have shown that the dead leaves SFR correlates well with sharpness/texture blur preference, and thus the target can potentially be used as a surrogate for more expensive subjective image quality evaluations. In this paper, the dead leaves target is analyzed for measurement of camera system spatial frequency response. It was determined that the power spectral density (PSD) of the ideal dead leaves target does not exhibit simple power law dependence, and scale invariance is only loosely obeyed. An extension to the ideal dead leaves PSD model is proposed, including a correction term to account for system noise. With this extended model, the SFR of several camera systems with a variety of The dead leaves model was recently introduced as a method for measuring the spatial frequency response (SFR) of camera systems. The target consists of a series of overlapping opaque circles with a uniform gray level distribution and radii distributed as r-3. Unlike the traditional knife-edge target, the SFR derived from the dead leaves target will be penalized for systems that employ aggressive noise reduction. Initial studies have shown that the dead leaves SFR correlates well with sharpness/texture blur preference, and thus the target can potentially be used as a surrogate for more expensive subjective image quality evaluations. In this paper, the dead leaves target is analyzed for measurement of camera system spatial frequency response. It was determined that the power spectral density (PSD) of the ideal dead leaves target does not exhibit simple power law dependence, and scale invariance is only loosely obeyed. An extension to the ideal dead leaves PSD model is proposed, including a correction term to account for system noise. With this extended model, the SFR of several camera systems with a variety of To view full papers go to www.imaging.org/ist/publications/reporter/index.cfm INSIDE THIS ISSUE Abstracts of Best Paper Awards . . . . . . . . . . . . 1s of Best Paper Awards . . . . . . . . . . . . 1 EI2010 Conference Report . . . . . . . . . . . . . . 3 Standards Update. . . . . . . . . . . . . . . . . . . . . 6 Vol. 25, No.2 March/April 2010