Marina Nicolas

The blur effect: perception and estimation with a new no-reference perceptual blur metric

To achieve the best image quality, noise and artifacts are generally removed at the cost of a loss of details generating the blur effect. To control and quantify the emergence of the blur effect, blur metrics have already been proposed in the literature. By associating the blur effect with the edge spreading, these metrics are sensitive not only to the threshold choice to classify the edge, but also to the presence of noise which can mislead the edge detection. Based on the observation that we have difficulties to perceive differences between a blurred image and the same reblurred image, we propose a new approach which is not based on transient characteristics but on the discrimination between different levels of blur perceptible on the same picture. Using subjective tests and psychophysics functions, we validate our blur perception theory for a set of pictures which are naturally unsharp or more or less blurred through one or two-dimensional low-pass filters. Those tests show the robustness and the ability of the metric to evaluate not only the blur introduced by a restoration processing but also focal blur or motion blur. Requiring no reference and a low cost implementation, this new perceptual blur metric is applicable in a large domain from a simple metric to a means to fine-tune artifacts corrections.

Metrics to Evaluate The Quality of Motion Compensation Systems in De-interlacing And Up-conversion Applications

Although motion compensation has improved a lot on natural videos, it still fails on sequences with erratic motions or mixed film-video content. This paper presents metrics to evaluate blur, combing artifacts, blockiness, halos and judder that remain typical limitations on such material even with state-of-the-art fallback policies.

Preserving color fidelity for display devices using scalable memory compression architecture for text, graphics, and video

High-end monitors and TVs based on LCD technology continue to increase their native display resolution to 4k by 2k and beyond. Subsequently, uncompressed pixel amplitude processing becomes costly not only when transmitting over cable or wireless communication channels, but also when processing with array processor architectures. For motion video content, spatial preprocessing from YCbCr 444 to YCbCr 420 is widely accepted. However, due to spatial low pass filtering in horizontal and vertical direction, quality and readability of small text and graphics content is heavily compromised when color contrast is high in chrominance channels. On the other hand, straight forward YCbCr 444 compression based on mathematical error coding schemes quite often lacks optimal adaptation to visually significant image content. We present a block-based memory compression architecture for text, graphics, and video enabling multidimensional error minimization with context sensitive control of visually noticeable artifacts. As a result of analyzing image context locally, the number of operations per pixel can be significantly reduced, especially when implemented on array processor architectures. A comparative analysis based on some competitive solutions highlights the effectiveness of our approach, identifies its current limitations with regard to high quality color rendering, and illustrates remaining visual artifacts.

Low-cost handling of combing artifacts in motion-compensated deinterlacing

This paper presents a new method to improve the combination of the motion-compensated field with the original field in deinterlacing applications. It is based on the direct detection of combing artifacts and on a new measurement for the vector reliability.

Improvement of conventional deinterlacing methods with extrema detection and interpolation

This article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system, typically a spatio-temporal motion adaptive one. The spatial interpolation part often fails to reconstruct close to horizontal lines with a proper continuity, leading to highly visible artifacts. Our system preserves the structure continuity taking into account that the mis-interpolated points usually correspond to local value extrema. The processing is based on chained lists and connected graph construction. The new interpolation method is restricted to such structures, for the rest of the image, a proper traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels affected by the extrema interpolation is relatively small, the overall image quality is subjectively well improved. Moreover, our solution allows to gain back one of the major advantages of motion compensation methods, without having to afford their complexity cost.

Color discrimination problems in digital TV systems

Color image artifacts become strongly noticeable as TV screens such as LCD flat panels or plasma displays grow in size and as consumers reach a higher level of image quality perception. At first we introduce you to visually noticeable color artifacts present in current digital TV systems, then we show how well they can be discriminated in different color spaces such as RGB or CIELAB and characterize their components. We also found a re-synthesized artifact helpful to elaborate an algorithm that reduces noticeable color artifacts to a level below the threshold of visual perception with regard to a reduced viewing distance.

Adaptive edge orientation analysis

This paper presents a method that detects edge orientations in still images. Edge orientation is a crucial information when one wants to optimize the quality of edges after different processings. The detection is carried out in the wavelet domain to take advantage of the multi-resolution features of the wavelet spaces, and locally adapts the resolution to the characteristics of edges. Our orientation detection method consists of finding the local direction along which the wavelet coefficients are the most regular. To do so, the image is divided in square blocks of varying size, in which Bresenham lines are drawn to represent different directions. The direction of the Bresenham line that contains the most regular wavelet coefficients, according to a criterion defined in the paper, is considered to be the direction of the edge inside the block. The choice of the Bresenham line drawing algorithm is justified in this paper, and we show that it considerably increases the angle precision compared to other methods as for instance, the method used for the construction of bandlet bases. An optimal segmentation is then computed in order to adapt the size of the blocks to the edge localization and to isolate in each block at most one contour orientation. Examples and applications on image interpolation are shown on real images.

Optimizing color fidelity for display devices using vectorized interpolation steered locally by perceptual error quantities

High-end PC monitors and TVs continue to increase their native display resolution to 4k by 2k and beyond. Subsequently, uncompressed pixel amplitude processing becomes costly not only when transmitting over cable or wireless communication channels, but also when processing with array processor architectures. We recently presented a block-based memory compression architecture for text, graphics, and video which we named parametric functional compression (PFC) enabling multi-dimensional error minimization with context sensitive control of visually noticeable artifacts. The underlying architecture was limited to small block sizes of 4x4 pixels. Although well suitable for random access, its overall compression ratio ranges between 1.5 and 2.0. To increase compression ratio as well as image quality, we propose a new hybrid approach. Within an extended block size we apply two complementary methods using a set of vectors with orientation and curvature attributes across a 3x3 kernel of pixel positions. The first method searches for linear interpolation candidate pixels that result in very low interpolation errors using vectorized linear interpolation (VLI). The second method calculates the local probability of orientation and curvature (POC) to predict and minimize PFC coding errors. Detailed performance estimation in comparison with the prior algorithm highlights the effectiveness of our new approach, identifies its current limitations with regard to high quality color rendering with lower number of bits per pixel, and illustrates remaining visual artifacts.

Image interpolation based on a multi-resolution directional map

This paper describes an interpolation method that takes into account the edge orientation in order to avoid typical interpolation artifacts (jagging, staircase effects...). It is first based on an edge orientation estimation, performed in the wavelet domain. The estimation uses the multi-resolution features of wavelets to give an accurate and non-biased description of the frequency characteristics of the edges, as well as their orientation. The interpolation is then performed, using the edge orientation estimation, to improve a reference interpolation (cubic-spline for instance). This improvement is carried out by filtering the edges with a Gaussian kernel along their direction in order to smooth the contour in the direction parallel to the edge, which avoids disturbing variations across them (jagging and staircase effects). This technique also keeps the sharpness of the transition in the direction perpendicular to the contour to avoid blur. Results are presented on both synthetic and real images, showing the visual impact of the presented method on the quality of interpolated images. Comparisons are made with the usual cubic-spline interpolation, and with other edge-directed interpolation techniques to discuss the choices that have been made in our method.