False Contour Reduction Research Articles

Reducing JPEG False Contour Using Visual Illumination

This paper presents an efficient and simple technique on reducing the false contour problem which often occurs in the JPEG decoded image. The false contour appears on JPEG decoded image while applying small quality factor. This problem induces unpleasant visual appearance. The proposed scheme exploits the usability of Halftoning-Based Block Truncation Coding (HBTC) approach on generating visual illumination to reduce the aforementioned problem. Three HBTC techniques, namely Ordered Dither Block Truncation Coding (ODBTC), Error Diffusion Block Truncation Coding (EDBTC) and Dot Diffused Block Truncation Coding (DDBTC), modify the DC components of all Discrete Cosine Transform (DCT) processed image on JPEG encoding stage. Experimental results show the proposed method superiority on JPEG false contour reduction. To further improve the JPEG decoded image quality, the proposed method utilizes the Gaussian kernel on replacing the DDBTC diffused kernel on spreading the error term. It assumes that the adjacent image blocks have a strong correlation in which high diffused coefficient should be applied on nearest adjacent neighbor. This paper extends the HBTC usability on JPEG false contour suppression.

False contour reduction using neural networks and adaptive bi-directional smoothing

The larger display devices, the more noticeable artifacts such as false contours, block artifacts, and other types of noises. This paper proposes a false contour reduction algorithm using neural networks (NNs) and adaptive bidirectional smoothing. The proposed algorithm consists of two parts: false contour detection and reduction parts. In the false contour detection part, false contour candidate pixels are detected using the directional contrast features. The false contour reduction part is composed of two steps: NN processing and bi-directional filtering. In the first step, false contours are reduced by pixelwise processing using NNs. In the second step, bi-directional smoothing is applied to a neighboring region of the false contour. Computer simulations with several test images show the effectiveness of the proposed false contour reduction algorithm in terms of the visual quality of result images, edge maps detected by Sobel masks, the peak signal-to-noise ratio, the structural similarity, and the computation time.

Reduction of halftoning errors due to line load in a plasma display panel

The displayed gray level of a plasma display panel (PDP) is often different from the intended target gray level because the displayed level is affected by line load (the number of on-cells in a scan line). Previous attempts to reduce this difference (i.e. error) have been applicable to PDPs with no constraint imposed on the on-off decision for each sub-field. In order to improve the image quality (e.g. dynamic false contour (DFC) reduction), recently-developed PDPs impose constraints on sub-field coding and reduce the number of gray levels. This paper proposes a new sub-field coding algorithm that compensates for level error caused by the load when constraints are imposed on sub-field coding. As the number of gray levels is reduced, halftoning is employed in order to represent intermediate gray levels. In the proposed algorithm, the magnitude of the level error caused by the load effect is predicted and then two levels that are used for the halftoning are modified to compensate for the error. The modified levels are the nearest levels to the input level among the levels that satisfy the constraint of the sub-field coding. In order to reduce errors with moderate computational complexity, error prediction and level update are repeated by twice. A significant error reduction is achieved and shown by simulation and experimentation using a 42-inch PDP, including a 93.5% reduction in the mean absolute error (MAE) in simulations and a 67.2% reduction in MAE in experiments on a PDP.

False contour reduction using directional dilation and edge-preserving filtering

As display devices have become larger, false contour artifacts invisible in small displays have appeared visible. False contours are artifacts that appear as step edges in relatively smooth regions of an image, mostly caused by image quantization. In this paper, a new false contour reduction algorithm of still images is proposed using directional dilation and edge-preserving filtering. The proposed algorithm consists of three steps: false contour detection, false contour map expansion, and edge-preserving false contour reduction. In the first step, pixels to be processed are detected and in the second step the processing area is expanded using the proposed directional dilation. Finally, only the pixels selected in the first two steps are filtered, in which edge-preserving filtering using multi-dimensional weight functions is employed. The performance of the proposed algorithm is compared with those of two existing methods. Experimental results in various aspects show that the proposed algorithm efficiently reduces false contours

Two-stage false contour detection using directional contrast features and its application to adaptive false contour reduction

In the era of digital television, artifacts such as false contours unnoticed in small television sets appear conspicuously as the size of display devices increases. This paper proposes a two-stage false contour detection algorithm and its application to false contour reduction. In stage 1 of false contour detection, smooth regions are first removed by bit-depth reduction or re-quantization. In stage 2, false contours are separated from edges or texture regions using directional contrast features, yielding the binary false contour decision map that shows possible candidate regions of false contours. Also a number of non-directional and directional features for possible false contour detection are considered and their performance is compared. For false contour reduction, variable-size directional smoothing is applied only to candidate regions that are specified by the false contour decision map. We use one-dimensional variable-size directional smoothing masks whose directions are orthogonal to the directions determined by the directional contrast features found in the false contour detection step. Computer simulations with several test images with various types of false contours show the effectiveness of the proposed false contour reduction algorithm in terms of visual quality and the peak signal-to-noise ratio. The proposed algorithm can also be used as a post-processing method for artifact reduction in various display devices.

A look‐up table based error diffusion algorithm for dynamic false contour reduction of plasma display panels

PDP(Plasma display panel) represents the gray levels by the pulse number modulation technique that results in undesirable dynamic false contours on moving images. This paper proposes a LUT(Look‐up table) based error diffusion algorithm for reduction of the dynamic false contours. A quantitative measure of the dynamic false contours is defined first. The measure of the dynamic false contours is calculated through simulation of every gray level combination of two consecutive frames. Based on the calculated measures, a modified gray level for a pair of gray levels of two consecutive frames is chosen to reduce the dynamic false contours. The chosen gray levels serve as contents of a gray level conversion LUT. Given a pair of gray levels of two consecutive frames, the gray level of current frame is modified based on the gray level conversion LUT. The new gray level is displayed on PDP. An error diffusion algorithm is, then, applied to compensate for the differences in the gray levels.