Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

/pdf/image-quality-assessment-from-error-visibility-to-structural-1rlwcqe34t.pdf

Image quality assessment: from error visibility to structural similarity

Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

http://ahvazdownload.persiangig.com/document/article/39.pdf

A wavelet tour of signal processing

In this article, we have reviewed the reasons why we (collectively) want to love or leave the venerable (but perhaps hoary) MSE. We have also reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems. The message we are trying to send here is not that one should abandon use of the MSE nor to blindly switch to any other particular signal fidelity measure. Rather, we hope to make the point that there are powerful, easy-to-use, and easy-to-understand alternatives that might be deployed depending on the application environment and needs. While we expect (and indeed, hope) that the MSE will continue to be widely used as a signal fidelity measure, it is our greater desire to see more advanced signal fidelity measures being used, especially in applications where perceptual criteria might be relevant. Ideally, the performance of a new signal processing algorithm might be compared to other algorithms using several fidelity criteria. Lastly, we hope that we have given further motivation to the community to consider recent advanced signal fidelity measures as design criteria for optimizing signal processing algorithms and systems. It is in this direction that we believe that the greatest benefit eventually lies.

Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures

Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.

Prediction of central nervous system embryonal tumour outcome based on gene expression

One of the aims of the standardization committee has been the development of Part I, which could be used on a royalty- and fee-free basis. This is important for the standard to become widely accepted. The standardization process, which is coordinated by the JTCI/SC29/WG1 of the ISO/IEC has already produced the international standard (IS) for Part I. In this article the structure of Part I of the JPFG 2000 standard is presented and performance comparisons with established standards are reported. This article is intended to serve as a tutorial for the JPEG 2000 standard. The main application areas and their requirements are given. The architecture of the standard follows with the description of the tiling, multicomponent transformations, wavelet transforms, quantization and entropy coding. Some of the most significant features of the standard are presented, such as region-of-interest coding, scalability, visual weighting, error resilience and file format aspects. Finally, some comparative results are reported and the future parts of the standard are discussed.

/pdf/the-jpeg-2000-still-image-compression-standard-2dd3aimci6.pdf

The JPEG 2000 still image compression standard

A shape can be more difficult to identify when other shapes are near it. For example, when several grating patches are viewed parafoveally, observers are unable to report the orientation of the central patch. This phenomenon, known as 'crowding,' has historically been confused with lateral masking, in which one stimulus attenuates signals generated by another stimulus. Here we show that despite their inability to report the orientation of an individual patch, observers can reliably estimate the average orientation, demonstrating that the local orientation signals are combined rather than lost. Our results imply that crowding is distinct from ordinary masking, and is perhaps related to texture perception. Under crowded conditions, the orientation signals in primary visual cortex are pooled before they reach consciousness.

/pdf/compulsory-averaging-of-crowded-orientation-signals-in-human-2y0lx65wyu.pdf

Compulsory averaging of crowded orientation signals in human vision

The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression, measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r2/sup -/spl lambda//, where r is the display visual resolution in pixels/degree, and /spl lambda/ is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

Visibility of wavelet quantization noise

We have implemented a model of contrast gain and control in human vision that incorporates a number of key features, including a contrast sensitivity function, multiple oriented bandpass channels, accelerating nonlinearities, and a devisive inhibitory gain control pool. The parameters of this model have been optimized through a fit to the recent data that describe masking of a Gabor function by cosine and Gabor masks [J. M. Foley, "Human luminance pattern mechanisms: masking experiments require a new model," J. Opt. Soc. Am. A 11, 1710 (1994)]. The model achieves a good fit to the data. We also demonstrate how the concept of recruitment may accommodate a variant of this model in which excitatory and inhibitory paths have a common accelerating nonlinearity, but which include multiple channels tuned to different levels of contrast.

/pdf/model-of-visual-contrast-gain-control-and-pattern-masking-25s9nu4m3x.pdf

Model of visual contrast gain control and pattern masking

For a patch of random visual texture embedded in a surrounding background of similar texture, we demonstrate that the perceived contrast of the texture patch depends substantially on the contrast of the background. When the texture patch is surrounded by high-contrast texture, the bright points of the texture patch appear dimmer, and simultaneously, its dark points appear less dark than when it is surrounded by a uniform background. The induced reduction of apparent contrast is greatly diminished when (i) the texture patch and background are filtered into nonoverlapping spatial frequency bands or (ii) the texture patch and background are presented to different eyes. Our results are unanticipated by all current theories of lightness perception and point to a perceptual mechanism for contrast gain control occurring at an early cortical or precortical neural locus.

https://www.pnas.org/content/pnas/86/23/9631.full.pdf

Texture interactions determine perceived contrast

WE hear periodic sounds, or tones, by means of parallel auditory filters, each tuned to a band of temporal frequency1, and we see periodic patterns, or gratings, by means of parallel visual filters, each tuned to a band of spatial frequency2. Beyond helping us to see gratings, do these visual filters participate in everyday tasks such as reading and object recognition? After all, grating visibility only requires the distinguishing of pattern from blank, whereas object recognition, for example letter identification, requires classification by the observer into one of many learned categories. Here we make use of results from hearing research3, applying to vision a noise-masking paradigm that reveals the filter(s) mediating any threshold task. We find that letter-identification and grating-detection filters are identical, showing that the recognition of these objects at one size is mediated and constrained by a single visual filter, or 'channel'.

Joshua A. Solomon

Papers

Compulsory averaging of crowded orientation signals in human vision

Visibility of wavelet quantization noise

Model of visual contrast gain control and pattern masking

Texture interactions determine perceived contrast

The visual filter mediating letter identification.