An edge classification based approach to the post-processing of transform encoded images

McDonnell, J.D.; Shorten, Robert; Fagan, Ailís

doi:10.1109/icassp.1994.389421

Cited by 13 publications

(7 citation statements)

References 4 publications

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“…[12][13][14] Nagin et al 4 describe an image segmentation procedure based on an analysis of histograms of local image regions. Their approach consists of a cascade of four processes; namely edge detection ͑Canny's 10 method͒, connectivitypreserving edge thinning, contour tracing, and dilation.…”

Section: Edge Classifiermentioning

confidence: 99%

“…[12][13][14] To reduce algorithm complexity, and computational requirements, a simple implementation of uniform quantization is commonly adopted in transform image coding schemes ͑including JPEG͒. Although this information is unrecoverable, it is possible, by introducing a carefully controlled, random dither signal during the decoding process, to reconstruct the transform coefficients such that, on average, they conform to a model of the average energy distribution of the transform coefficients prior to quantization.…”

Section: Cosine Transform Domain Dithermentioning

confidence: 99%

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Postprocessing of transform coded images via histogram-based edge classification

McDonnell

Shorten²,

Fagan

1997

J. Electron. Imaging

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Quantization noise prevalent in transform encoded images becomes increasingly objectionable as the required bit rate for the compressed image representation is reduced. The perceptual effect of this coding noise is not uniform throughout the image, however, being highly dependent on the local behavior of the signal on which it is superimposed. An adaptive, nonlinear postprocessing algorithm is described, which is shown to appreciably enhance the subjective quality of the reconstructed image. A three-component image model is adopted, according to which any image is considered to be composed of nonoverlapping strong edge, textured, and monotone components. The foundation of the postprocessing algorithm is a computationally efficient edge classifier capable of resolving an image into its three components. The classifier operates by exploiting the characteristic shape of the histogram of pixel luminance values in a strong edge region to distinguish between strong and textured edges. The postprocessing algorithm consists of a combination of adaptive, ␣ trimmed mean filtering (where the ␣ value and window size are determined by the output of the edge classifier) and a cosine transform domain dithering technique. The results presented confirm the efficacy of the proposed approach. © 1997 SPIE and IS&T.

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Section: Edge Classifiermentioning

confidence: 99%

Section: Cosine Transform Domain Dithermentioning

confidence: 99%

Postprocessing of transform coded images via histogram-based edge classification

McDonnell

Shorten²,

Fagan

1997

J. Electron. Imaging

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“…For instance, Reeve and Lim proposed a symmetric two-dimensional Gaussian spatial filtering method to reduce the blocking artifacts [16]. Other methods of spatial-domain techniques are also reported in the literature, based on gradients/thresholds and the histogram which first classify the blocks as ei ther high frequency or low frequency, followed by filtering to remove artifacts [18]- [23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Type-2 Fuzzy Directed Hybrid Post-Filtering Technique for Efficient JPEG Image Artifact Reduction

Thakur

Gupta

2021

Design, Construction, Maintenance

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Image and video compression becomes very popular and intense field in recent decades, due to their fast and quality communication demand. To cope up with the high speed communication demand of image and videos, over the communication channel, higher compression (ie. low bit rate compression) is now preferred at the cost of quality degradation. Currently JPEG and JPEG2000 are the most popularly used codec’s for achieving quality image compression. Practically, on the low bit rate compression, it has been observed that, the JPEG standard compressed images suffer from multifarious visual distortions. To address this problem effectively, this paper proposed an innovative type-2 fuzzy directed hybrid post filtering technique, which is framed to suppress the artifacts generated in JPEG compressed images at low bit rate compression. The proposed technique addresses all three types of JPEG compressed image artifacts: blocking, edges blurring, and aliasing. Furthermore the proposed technique is structured with two stages, to enhance the quality of JPEG compressed images. The first stage, removes blocking artifacts using boundary smoothing and guided filtering techniques. The second stage reduces blurring and aliasing around the edges through type-2 fuzzy directed local edge regeneration. To prove higher efficiency of proposed work, a complete comparative performance evaluation with other existing JPEG artifact removal techniques, has also presented. This extensive performance analysis includes visual quality assessment of post-filtered images along with subjective quality assessment on the basis of, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). Performance evaluation illustrates that the, proposed approach is efficient, provides PSNR improvement of approximately 1 dB along with higher reduction in MSE values as compared to state of the art algorithms for all the bit-rate compressions.

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“…These methods can be classified as spatial filtering [1][2][3][4][5] and DCT-based 6-14 methods. Reeve and Lim's method, 1 a symmetric, 2-D Gaussian spatial filter, has the drawback of visible smoothing of the image.…”

Section: Introductionmentioning

confidence: 99%

“…There have been many attempts [1][2][3][4][5][6][7][8][9][10][11][12][13][14] to reduce blocking artifacts in images. These methods can be classified as spatial filtering [1][2][3][4][5] and DCT-based 6-14 methods.…”

Section: Introductionmentioning

confidence: 99%

Novel artifact removal algorithm in the discrete cosine transform domain

Chang

2008

J. Electron. Imaging

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The blocking effect is the major drawback in discrete cosine transform (DCT)-based codecs at low bit rates. When a high compression ratio is required, boundaries between adjacent image blocks become visible. This kind of degradation probably will affect the judgment of an end user. In this work, a four-neighboring-block zero-masking technique is proposed in the DCT frequency domain. The proposed algorithm uses a shift block within four adjacent DCT blocks to reduce computational complexity. By slightly modifying several DCT coefficients in the shift block, the artifacts that result from quantization and dequantization processes are alleviated. The simulation results show that both visual perception and objective image quality are noticeably improved.

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An edge classification based approach to the post-processing of transform encoded images

Cited by 13 publications

References 4 publications

Postprocessing of transform coded images via histogram-based edge classification

Postprocessing of transform coded images via histogram-based edge classification

A Novel Type-2 Fuzzy Directed Hybrid Post-Filtering Technique for Efficient JPEG Image Artifact Reduction

Novel artifact removal algorithm in the discrete cosine transform domain

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