Blocking artifacts continue to be among the most serious defects that occur in images and video streams compressed to low bit rates using block discrete cosine transform (DCT)-based compression standards (e.g., JPEG, MPEG, and H.263). It is of interest to be able to numerically assess the degree of blocking artifact in a visual signal, for example, in order to objectively determine the efficacy of a compression method, or to discover the quality of video content being delivered by a web server. We propose new methods for efficiently assessing, and subsequently reducing, the severity of blocking artifacts in compressed image bitstreams. The method is blind, and operates only in the DCT domain. Hence, it can be applied to unknown visual signals, and it is efficient since the signal need not be compressed or decompressed. In the algorithm, blocking artifacts are modeled as 2-D step functions. A fast DCT-domain algorithm extracts all parameters needed to detect the presence of, and estimate the amplitude of blocking artifacts, by exploiting several properties of the human vision system. Using the estimate of blockiness, a novel DCT-domain method is then developed which adaptively reduces detected blocking artifacts. Our experimental results show that the proposed method of measuring blocking artifacts is effective and stable across a wide variety of images. Moreover, the proposed blocking-artifact reduction method exhibits satisfactory performance as compared to other post-processing techniques. The proposed technique has a low computational cost hence can be used for real-time image/video quality monitoring and control, especially in applications where it is desired that the image/video data be processed directly in the DCT-domain.

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Efficient DCT-domain blind measurement and reduction of blocking artifacts

This paper proposes a novel postprocessing technique for reducing blocking artifacts in low-bit-rate transform-coded images. The proposed approach works in the transform domain to alleviate the accuracy loss of transform coefficients, which is introduced by the quantization process. The masking effect in the human visual system (HVS) is considered, and an adaptive weighting mechanism is then integrated into the postfiltering. In low-activity areas, since blocking artifacts appear to be perceptually more detectable, a large window is used to efficiently smooth out the artifacts. In order to preserve image details, a small mask, as well as a large central weight, is employed for processing those high-activity blocks, where blocking artifacts are less noticeable due to the masking ability of local background. The quantization constraint is finally applied to the postfiltered coefficients. Experimental results show that the proposed technique provides satisfactory performance as compared to other postfilters in both objective and subjective image quality.

Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts

Since the publication of Wireless Video Communications five years ago, the area of video compression and wireless transceivers has evolved even further. This new edition addresses a range of recent developments in these areas, giving cognizance to the associated transmission aspects and issues of error resilience. Video Compression and Communications has been updated and condensed yet remains all-encompassing, giving a comprehensive overview of the subject. Covering compression issues, coding delay, implementational complexity and bitrate, the book also looks at the historical perspective to video communication. New edition of successful and informative text, Wireless Video Communications Substantial new material has been added on areas such as H.264, MPEG4 coding and transceivers Clear presentation and broad scope make it essential for anyone interested in wireless communications Systematically converts the lessons of Shannon's information theory into design principles applicable to practical wireless systems. This book is ideal for postgraduates and researchers in communication systems but will also be a valuable reference to undergraduates, development and systems engineers of video compression applications as well as industrialists, managers and visual communications practitioners.

Video Compression and Communications: From Basics to H.261, H.263, H.264, MPEG4 for DVB and HSDPA-Style Adaptive Turbo-Transceivers

Since the postprocessing of coded images using a priori information depends on the constraints imposed on the coded images, it is important to utilize constraints that are best suited to postprocessing techniques Among the constraint sets, the quantization constraint set (QCS) is commonly used in the iterative algorithms that are especially based on the theory of projections onto convex sets (POCS) The converged image in the iteration is usually a boundary point of the QCS But, we can easily conjecture that the possible location of the original image is inside the QCS In order to obtain an image inside the QCS, we proposed a new convex constraint set, a subset of the QCS called narrow QCS (NQCS) as a substitute for the QCS In order to demonstrate that the NQCS works better than the QCS on natural images, we present mathematical analysis with examples and simulations by reformulating the iterative algorithm of the constrained minimization problem or of the POCS using the probability theory Since the initial image of the iteration is the centroid of the QCS, we reach a conclusion that the first iteration is enough to recover the coded image, which implies no need of any theories that guarantee the convergences

Theory of projection onto the narrow quantization constraint set and its application

This paper presents the local cosine transform (LCT) as a new method for the reduction and smoothing of the blocking effect that appears at low bit rates in image coding algorithms based on the discrete cosine transform (DCT). In particular, the blocking effect appears in the JPEG baseline sequential algorithm. Two types of LCT were developed: LCT-IV is based on the DCT type IV, and LCT-II is based on DCT type II, which is known as the standard DCT. At the encoder side the image is first divided into small blocks of pixels. Both types of LCT have basis functions that overlap adjacent blocks. Prior to the DCT coding algorithm a preprocessing phase in which the image is multiplied by smooth cutoff functions (or bells) that overlap adjacent blocks is applied. This is implemented by folding the overlapping parts of the bells back into the original blocks, and thus it permits the DCT algorithm to operate on the resulting blocks. At the decoder side the inverse LCT is performed by unfolding the samples back to produce the overlapped bells. The purpose of the multiplication by the bell is to reduce the gaps and inaccuracies that may be introduced by the encoder during the quantization step. LCT-IV and LCT-II were applied on images as a preprocessing phase followed by the JPEG baseline sequential compression algorithm. For LCT-IV, the DCT type IV replaced the standard DCT as the kernel of the transform coding. In both cases, for the same low bit rates the blocking effect was smoothed and reduced while the image quality in terms of mean-square error became better. Subjective tests performed on a group of observers also confirm these results. Thus the LCT can be added as an optional step for improving the quality of existing DCT (JPEG) encoders. Advantages over other methods that attempt to reduce the blocking effect due to quantization are also described.

Local cosine transform: a method for the reduction of the blocking effect in JPEG

A method of coding images based on interleaved blocks is proposed. These block have irregular outlines with both holes and islands. It is shown that if they are designed by the application of ‘n-cycles’ to a rectangular array, the resulting block shapes interleave perfectly without overlap. Used in transform coding, they substantially reduce the visiblity of block structure at low data rates. Experimental investigations are reported which identified desirable properties of interleaved blocks, in terms of their degree of overlap and interior distribution of pels. The pre-and post-transformations associated with the use of such blocks are easily accomplished by a simple modification of pel addressing routines, this being the only processing overhead incurred. Limited experiments on another form of overlapping block, which merged rather than interleaved with its neighbours, are also reported. These were computationally more involved and tended to magnify interblock contrasts.

Transform coding of images using interleaved blocks

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Transform coding of images using interleaved blocks