Perceptual quality metrics applied to still image compression

We present a review of perceptual image quality metrics and their application to still image compression. The review describes how image quality metrics can be used to guide an image compression scheme and outlines the advantages, disadvantages and limitations of a number of quality metrics. We examine a broad range of metrics ranging from simple mathematical measures to those which incorporate full perceptual models. We highlight some variation in the models for luminance adaptation and the contrast sensitivity function and discuss what appears to be a lack of a general consensus regarding the models which best describe contrast masking and error summation. We identify how the various perceptual components have been incorporated in quality metrics, and identify a number of psychophysical testing techniques that can be used to validate the metrics. We conclude by illustrating some of the issues discussed throughout the paper with a simple demonstration. (C) 1998 Elsevier Science B.V. All rights reserved.

Parallel processing and image analysis in the eyes of mantis shrimps

The compound eyes of mantis shrimps, a group of tropical marine crustaceans, incorporate principles of serial and parallel processing of visual information that may be applicable to artificial imaging systems. Their eyes include numerous specializations for analysis of the spectral and polarizational properties of light, and include more photoreceptor classes for analysis of ultraviolet light, color, and polarization than occur in any other known visual system. This is possible because receptors in different regions of the eye are anatomically diverse and incorporate unusual structural features, such as spectral filters, not seen in other compound eyes. Unlike eyes of most other animals, eyes of mantis shrimps must move to acquire some types of visual information and to integrate color and polarization with spatial vision. Information leaving the retina appears to be processed into numerous parallel data streams leading into the central nervous system, greatly reducing the analytical requirements at higher levels. Many of these unusual features of mantis shrimp vision may inspire new sensor designs for machine vision

3D reconstruction and quantification of macropores using X-ray computed tomography and image analysis

Axial X-ray Computed tomography (CT) scanning provides a convenient means of recording the three-dimensional form of soil structure. The technique has been used for nearly two decades, but initial development has concentrated on qualitative description of images. More recently, increasing effort has been put into quantifying the geometry and topology of macropores likely to contribute to preferential now in soils. Here we describe a novel technique for tracing connected macropores in the CT scans. After object extraction, three-dimensional mathematical morphological filters are applied to quantify the reconstructed structure. These filters consist of sequences of so-called erosions and/or dilations of a 32-face structuring element to describe object distances and volumes of influence. The tracing and quantification methodologies were tested on a set of undisturbed soil cores collected in a Swiss pre-alpine meadow, where a new earthworm species (Aporrectodea nocturna) was accidentally introduced. Given the reduced number of samples analysed in this study, the results presented only illustrate the potential of the method to reconstruct and quantify macropores. Our results suggest that the introduction of the new species induced very limited chance to the soil structured for example, no difference in total macropore length or mean diameter was observed. However. in the zone colonised by, the new species. individual macropores tended to have a longer average length. be more vertical and be further apart at some depth. Overall, the approach proved well suited to the analysis of the three-dimensional architecture of macropores. It provides a framework for the analysis of complex structures, which are less satisfactorily observed and described using 2D imaging. (C) 2002 Elsevier Science B.V. All rights reserved.

Assessment of image quality of a standard and two dose-reducing protocols in paediatric pelvic CT

Background: Concerns exist regarding the effect of radiation dose from paediatric pelvic CT scans and the potential later risk of radiation-induced neoplasm and teratogenic outcomes in these patients. Objective: To assess the diagnostic quality of CT images of the paediatric pelvis using either reduced mAs or increased pitch compared with standard settings. Materials and methods: A prospective study of pelvic CT scans of 105 paediatric patients was performed using one of three protocols: (1) 31 at a standard protocol of 200 mA with rotation time of 0.75 s at 120 kVp and a pitch factor approximating 1.4; (2) 31 at increased pitch factor approaching 2 and 200 mA; and (3) 43 at a reduced setting of 100 mA and a pitch factor of 1.4. All other settings remained the same in all three groups. Image quality was assessed by radiologists blinded to the protocol used in each scan. Results: No significant difference was found between the quality of images acquired at standard settings and those acquired at half the standard mAs. The use of increased pitch factor resulted in a higher proportion of poor images. Conclusions: Images acquired at 120 kVp using 75 mAs are equivalent in diagnostic quality to those acquired at 150 mAs. Reduced settings can provide useful imaging of the paediatric pelvis and should be considered as a standard protocol in these situations.

Characterisation of the three-dimensional structure of earthworm burrow systems using image analysis and mathematical morphology

The aim of this work was to exemplify the specific contribution of both two- and three-dimensional (31)) X-ray computed tomography to characterise earthworm burrow systems. To achieve this purpose we used 3D mathematical morphology operators to characterise burrow systems resulting from the activity of an anecic (Aporrectodea noctunia), and an endogeic species (Allolobophora chlorotica), when both species were introduced either separately or together into artificial soil cores. Images of these soil cores were obtained using a medical X-ray tomography scanner. Three-dimensional reconstructions of burrow systems were obtained using a specifically developed segmentation algorithm. To study the differences between burrow systems, a set of classical tools of mathematical morphology (granulometries) were used. So-called granulometries based on different structuring elements clearly separated the different burrow systems. They enabled us to show that burrows made by the anecic species were fatter, longer, more vertical, more continuous but less sinuous than burrows of the endogeic species. The granulometry transform of the soil matrix showed that burrows made by A. nocturna were more evenly distributed than those of A. chlorotica. Although a good discrimination was possible when only one species was introduced into the soil cores, it was not possible to separate burrows of the two species from each other in cases where species were introduced into the same soil core. This limitation, partly due to the insufficient spatial resolution of the medical scanner, precluded the use of the morphological operators to study putative interactions between the two species.

Image calibration to like-values in mapping shallow water quality from multitemporal data

The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).