Scott J. Daly

Visible differences predictor: an algorithm for the assessment of image fidelity

Image fidelity is the subset of overall image quality that specifically addresses the visual equivalence of two images. This paper describes an algorithm for determining whether the goal of image fidelity is met as a function of display parameters and viewing conditions. Using a digital image processing approach, this algorithm is intended for the design and analysis of image processing algorithms, imaging systems, and imaging media. The visual model, which is the central component of the algorithm, is comprised of three parts: an amplitude nonlinearity, a contrast sensitivity function, and a hierarchy of detection mechanisms.

A visual model for optimizing the design of image processing algorithms

The paper describes an algorithm for the assessment of image fidelity. The algorithm includes an image processing model of the human visual system for luminance still imagery. The major components of the algorithm are described that model the visual system as three main sensitivity variations. These address the sensitivity as a function of gray level, as a function of spatial frequency, and as a function of image content. To quantify the performance of the algorithm, specific psychophysical experiments were simulated, and these results are shown.<<ETX>>

Uniform Perceptual Quantization: Applications to Digital Radiography

The principle involved in the uniform quantization of perceived lightness is considered in the context of digital radiography. Its effects on the visibility of quantization noise (contouring artifacts) are investigated both analytically and experimentally. Several visual system models of perceived lightness as a function of stimulus luminance are used. These include a logarithmic model, various power function models, and cone models. The results can be extended for other digital imaging modalities.

Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

Comparative study of wavelet and discrete cosine transform (DCT) decompositions with equivalent quantization and encoding strategies for medical images

Wavelet-based image compression is receiving significant attention, largely because of its potential for good image quality at low bit rates. In medical applications, low bit rate coding may not be the primary concern, and it is not obvious that wavelet techniques are significantly superior to more established techniques at higher quality levels. In this work we present a straightforward comparison between a wavelet decomposition and the well-known discrete cosine transform decomposition (as used in the JPEG compression standard), using comparable quantization and encoding strategies to isolate fundamental differences between the two methods. Our focus is on the compression of single-frame, monochrome images taken from several common modalities (chest and bone x-rays and mammograms).

Display of medical images on CRT soft-copy displays: a tutorial

Medical images are increasingly being presented on soft-copy displays such as CRTs but without, in our opinion, consistent visualization of the medical image data. Reaction to earlier calls for implementing a display standard for medical images has been slow. This has prompted us to write a tutorial which we hope will accelerate the acceptance of standardized image presentation on soft-copy displays in electronic radiology. The types of medical images and their visualization (luminance tone scale and dynamic range) are discussed. The impact of ambient lighting on the observed tone scale is also analyzed. Since the human observer is the detector of medical images, we review the critical parameters that characterize the human visual system, HVS [H. Blume, S. Daly, and E. Muka, Presentation of Medical Images on CRT Displays -- A Renewed Proposal for a Display Function Standard, Proc. SPIE Vol. 1897 Image Capture, Formatting, and Display, pp. 215 - 231, (1993)]. We provide additional information regarding the proposed mathematical representation of the HVS `display function and threshold contrast modulation and show how they are related. We discuss the differences between the desired visualization of a set of medical data versus the display function of a soft-copy display such as a CRT. To facilitate the objective that images can be consistently rendered, we repeat our call for a standardized display function for soft- copy displays and believe that is should be based on the HVS. We discuss which medical image data should be perceptually linearized throughout the medical data dynamic range. These points are demonstrated using typical CT images and digitized projection radiographs presented with different gray scales.

Presentation of medical images on CRT displays: a renewed proposal for a display function standard

A mathematically defined standard display function is proposed for black-and-white hard and soft-copy image displays based on perceptual linearization. Since perceptual linearization is related to threshold contrast of targets with specific parameters, perceptually linearized display functions are calculated for a variety of target descriptors to illustrate the range of linearization by the proposed standard. Rogers and Carels formula and the two-dimensional models of visual system sensitivity of Barten and Daly are used to calculate such display functions. The proposed standard provides perceptual linearization for the peak contrast sensitivity near 4 c/deg. The standard is adaptable to black-and-white display systems independent of maximum luminance and luminance range. Perceptual linearization is maintained largely independent of object size, external noise, observer performance variations, low supra-threshold contrast, target orientation, and ambient light. The standard facilitates similarity between the soft and hard-copy of an image independent of luminance. When using the standard function for displaying images, a minimum number of bits for the D/A converter is required that provides uniform digitization resolution over the entire display range. The standard display function, however, is not a visualization standard for images of specific applications.

An Optimized Image Data Compression Technique Utilized In The Kodak Sv9600 Still Video Transceiver

The Kodak still video transceiver system is designed to electronically transmit and receive high quality color video images over standard telephone lines. A detailed description of the algorithm used in compressing the digital image data is provided. The algorithm is based on the discrete cosine transform (DCT) and uses human visual system (HVS) sensitivity models to achieve high compression ratios without visible artifacts.

8.3: Visual Modeling of Upscaled Image Discrimination

This paper describes the application of a visual model to the spatial upsampling problem. The visual model includes an updated optical pointspread function that is adapted to a particular displays spectral emission characteristics. The visual model identifies locations of visible differences between high resolution groundtruth and 2X upsampled images, and allows quantifying the degree of difference between competing algorithms. Subjectivelydetermined image difference thresholds are compared to model predictions for both upsampsled Bluray and highresolution still images.

Modulator-induced streaking artifact in laser film printer images

The visibility of the modulatorinduced streaking artifact in the images from a laser film printer has been observed and analyzed. These streaks which occur in the printing of a light (low density) area after the printing of a dark (high density) area can be ascribed to the reflection of acoustic power in the acoustooptic modulator. By comparing the fractional transmission change in the light area (due to the reflection of acoustic power used for the printing of the dark area) with a visual threshold contrast the visibility of streaks can be determined. These results are found to be in good agreement with experiments. Specifications on the maximum acoustic reflection coefficient for the suppression of streaking visibility are also given. 1.