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Grayscale

About: Grayscale is a research topic. Over the lifetime, 13278 publications have been published within this topic receiving 156084 citations. The topic is also known as: grayscale image & black-and-white image.


Papers
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Journal ArticleDOI
TL;DR: It was found that measures based on the phase spectrum, the multireso- lution distance or the HVS filtered mean square error are computa- tionally simple and are more responsive to coding artifacts.
Abstract: In this work we comprehensively categorize image qual- ity measures, extend measures defined for gray scale images to their multispectral case, and propose novel image quality measures. They are categorized into pixel difference-based, correlation-based, edge-based, spectral-based, context-based and human visual sys- tem (HVS)-based measures. Furthermore we compare these mea- sures statistically for still image compression applications. The sta- tistical behavior of the measures and their sensitivity to coding artifacts are investigated via analysis of variance techniques. Their similarities or differences are illustrated by plotting their Kohonen maps. Measures that give consistent scores across an image class and that are sensitive to coding artifacts are pointed out. It was found that measures based on the phase spectrum, the multireso- lution distance or the HVS filtered mean square error are computa- tionally simple and are more responsive to coding artifacts. We also demonstrate the utility of combining selected quality metrics in build- ing a steganalysis tool. © 2002 SPIE and IS&T.

661 citations

Book ChapterDOI
26 Jun 2000
TL;DR: This paper presents a theoretically very simple yet efficient approach for gray scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions, which is very robust in terms of gray scale variations, since the operators are by definition invariant against any monotonic transformation of the gray scale.
Abstract: This paper presents a theoretically very simple yet efficient approach for gray scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions The proposed approach is very robust in terms of gray scale variations, since the operators are by definition invariant against any monotonic transformation of the gray scale Another advantage is computational simplicity, as the operators can be realized with a few operations in a small neighborhood and a lookup table Excellent experimental results obtained in two true problems of rotation invariance, where the classifier is trained at one particular rotation angle and tested with samples from other rotation angles, demonstrate that good discrimination can be achieved with the statistics of simple rotation invariant local binary patterns These operators characterize the spatial configuration of local image texture and the performance can be further improved by combining them with rotation invariant variance measures that characterize the contrast of local image texture The joint distributions of these orthogonal measures are shown to be very powerful tools for rotation invariant texture analysis

646 citations

Journal ArticleDOI
TL;DR: In this Letter, a new image encryption scheme is presented, in which shuffling the positions and changing the grey values of image pixels are combined to confuse the relationship between the cipher-image and the plain-image.

644 citations

Journal ArticleDOI
TL;DR: In this article, a new underwater color image quality evaluation (UCIQE) metric is proposed to quantify the non-uniform color cast, blurring, and low contrast that characterize underwater engineering and monitoring images.
Abstract: Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

638 citations

Journal ArticleDOI
TL;DR: The biomimetic CMOS dynamic vision and image sensor described in this paper is based on a QVGA array of fully autonomous pixels containing event-based change detection and pulse-width-modulation imaging circuitry, which ideally results in lossless video compression through complete temporal redundancy suppression at the pixel level.
Abstract: The biomimetic CMOS dynamic vision and image sensor described in this paper is based on a QVGA (304×240) array of fully autonomous pixels containing event-based change detection and pulse-width-modulation (PWM) imaging circuitry. Exposure measurements are initiated and carried out locally by the individual pixel that has detected a change of brightness in its field-of-view. Pixels do not rely on external timing signals and independently and asynchronously request access to an (asynchronous arbitrated) output channel when they have new grayscale values to communicate. Pixels that are not stimulated visually do not produce output. The visual information acquired from the scene, temporal contrast and grayscale data, are communicated in the form of asynchronous address-events (AER), with the grayscale values being encoded in inter-event intervals. The pixel-autonomous and massively parallel operation ideally results in lossless video compression through complete temporal redundancy suppression at the pixel level. Compression factors depend on scene activity and peak at ~1000 for static scenes. Due to the time-based encoding of the illumination information, very high dynamic range - intra-scene DR of 143 dB static and 125 dB at 30 fps equivalent temporal resolution - is achieved. A novel time-domain correlated double sampling (TCDS) method yields array FPN of 56 dB (9.3 bit) for >10 Lx illuminance.

632 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023377
20221,015
2021534
2020787
20191,156
20181,192