Fast Blind Measurement of Blocking Artifacts in both Pixel and DCT Domains

Park, Chun-Su; Kim, Jun-Hyung; Ko, Sung-Jea

doi:10.1007/s10851-007-0019-4

Cited by 20 publications

(37 citation statements)

References 12 publications

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“…A weighted Sobel operator-based blocking method is presented in [53], in which the computation involves luminance gradient matrices of DCT-coded images. A method where a rather simple approach of taking abrupt change in pixel values as a signal of blocking has been proposed in [54] and it can be implemented both in pixel and DCT domain, and a method of blockiness estimation in natural scene JPEG compressed images has been presented in [55] which was influenced by the impact of multineural channels pattern of HVS for vision sensing.…”

Section: Blockingmentioning

confidence: 99%

No-reference image and video quality assessment: a classification and review of recent approaches

et al. 2014

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The field of perceptual quality assessment has gone through a wide range of developments and it is still growing. In particular, the area of no-reference (NR) image and video quality assessment has progressed rapidly during the last decade. In this article, we present a classification and review of latest published research work in the area of NR image and video quality assessment. The NR methods of visual quality assessment considered for review are structured into categories and subcategories based on the types of methodologies used for the underlying processing employed for quality estimation. Overall, the classification has been done into three categories, namely, pixel-based methods, bitstream-based methods, and hybrid methods of the aforementioned two categories. We believe that the review presented in this article will be helpful for practitioners as well as for researchers to keep abreast of the recent developments in the area of NR image and video quality assessment. This article can be used for various purposes such as gaining a structured overview of the field and to carry out performance comparisons for the state-of-the-art methods. Keywords:No-reference; Image quality assessment; Video quality assessment; Perceptual quality 1 Review IntroductionThere has been a tremendous progress recently in the usage of digital images and videos for an increasing number of applications. Multimedia services that have gained wide interest include digital television broadcasts, video streaming applications, and real-time audio and video services over the Internet. The global mobile data traffic grew by 81% in 2013, and during 2014, the number of mobileconnected devices will exceed the number of people on earth, according to predictions made by Cisco. The video portion of the mobile data traffic was 53% in 2013 and is expected to exceed 67% by 2018 [1]. With this huge increase in the exposure of image and video to the human eye, the interest in delivering quality of experience (QoE) may increase naturally. The quality of visual media can get degraded during capturing, compression, transmission, reproduction, and displaying due to the distortions that might occur at any of these stages. The legitimate judges of visual quality are humans as end users, the opinions of whom can be obtained by subjective experiments. Subjective experiments involve a panel of participants which are usually non-experts, also referred to as test subjects, to assess the perceptual quality of given test material such as a sequence of images or videos. Subjective experiments are typically conducted in a controlled laboratory environment. Careful planning and several factors including assessment method, selection of test material, viewing conditions, grading scale, and timing of presentation have to be considered prior to a subjective experiment. For example, Recommendation (ITU-R) BT.500 [2] provides detailed guidelines for conducting subjective experiments for the assessment of quality of television pictures. The outcomes of a subjectiv...

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Section: Blockingmentioning

confidence: 99%

No-reference image and video quality assessment: a classification and review of recent approaches

et al. 2014

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“…The correlation between the intensity values of the boundary pixels of two neighboring blocks in the DCT domain is used to distinguish between smooth and non smooth regions. Wang et al (2004) [7]utilized Walsh Transform to form a DC Image for obtaining the edge distribution in the original Image. An adaptive filter and compensatory matrices are used to overcome the drawback of previous algorithm.…”

Section: Frequency Domain Techniquesmentioning

confidence: 99%

“…An adaptive filter and compensatory matrices are used to overcome the drawback of previous algorithm. The weakness of Wang et al (2004) [7] is to assume that the difference of the pixel values in the block boundary is caused by only the blocking artifacts. Wei et al (2005) [8] proposed odd tile length low pass first (OTLPF) convention.…”

Section: Frequency Domain Techniquesmentioning

confidence: 99%

“…The proposed method reduces the artifacts to great extent while preserving the image information. Park et al (2007) [12] proposed method that can measure the blocking artifacts in both pixel and DCT domain with low computational complexity. The proposed method measures true blocking artifacts using the original image and can be used to improve the performance of existing algorithms by reducing the blocking artifacts.…”

Section: Frequency Domain Techniquesmentioning

confidence: 99%

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Frequency Domain Techniques For Blocking Artifact Reduction-A Review

Singh¹

2016

IJECS

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Block-based coding is used extensively both in image and video coding systems. Image coding systems that divide an image into sub-images have problems in very low bit rate applications. In low bit rate applications, this scheme gives rise to "blocking artifacts" that arise due to image segmentation which severely reduce the visual quality of an image or video. Reducing blocking artifacts is essential to render the compressed visual data acceptable to the viewer. Various deblocking methods have been proposed in the literature to reduce blocking artifacts. Many of these methods are based on the post-processing at the encoding side. In the presentresearch paper various deblocking methods applied in the frequency domain are discussed.

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“…This paper focuses on blockiness due to its importance in image and video compression, enhancement, and quality assessment. Several no-reference blockiness metrics have been proposed in the literature [4][5][6][7][8][9][10][11][12][13][14][15][16][17]. However, most of the existing no-reference blockiness metrics neglect the important influences of grid distortions of an image on the performance of the metric.…”

Section: Introductionmentioning

confidence: 99%

Blind blockiness measure based on marginal distribution of wavelet coefficient and saliency

Ryu

Sohn

2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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The objective measurement of blockiness plays an important role in many applications, such as the quality assessment of an image, and the design of image and video coding system. However, most of the existing no-reference blockiness metrics do not consider important influences of grid distortion of an image on the performance of the metric. In this paper, we propose a new blockiness metric, which is robust to grid distortion, based on the marginal distribution of local wavelet coefficients and saliency information. Experiments for several public image databases showed that the proposed metric provides consistent correlations with subjective blockiness scores and outperforms other existing no-reference blockiness metrics.

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Fast Blind Measurement of Blocking Artifacts in both Pixel and DCT Domains

Cited by 20 publications

References 12 publications

No-reference image and video quality assessment: a classification and review of recent approaches

No-reference image and video quality assessment: a classification and review of recent approaches

Frequency Domain Techniques For Blocking Artifact Reduction-A Review

Blind blockiness measure based on marginal distribution of wavelet coefficient and saliency

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