Stefano Marsi

A simple edge-sensitive image interpolation filter

A novel scheme for edge-preserving image interpolation is introduced, which is based on the use of a simple nonlinear filter which accurately reconstructs sharp edges. Simulation results show the superior performances of the proposed approach with respect to other interpolation techniques.

A Simple Algorithm For The Reduction Of Blocking Artifacts In Images And Its Implementation

A simple but effective operator for the reduction of blocking artifacts is presented, together with a simple hardware implementation. The method is based on the rational filter approach: the operator is expressed as a ratio between a linear and a polynomial function of the input data. Such filters have been proved to outperform other conventional methods in other applications, such as noise smoothing, thanks to their capability of adapting gradually to the local image characteristics. The filter is capable of biasing its behaviour in order to achieve good performance both in uniform areas, where linear smoothing is needed, and in textured zones, where nonlinear and directional filtering is required. An activity detector is embedded in the expression of the operator itself so that the biasing of the behaviour of the filter is smooth and not based on fixed thresholds. A solution for the hardware implementation of the scheme is presented in detail. Despite the simplifications imposed by the hardware design, the filter retains the same efficiency as the original algorithm.

Application-Specific Instruction-Set Processor for Retinex-Like Image and Video Processing

This brief presents an application-specific instruction-set processor (ASIP) for real-time Retinex image and video filtering. Design optimizations are addressed at algorithmic and architectural levels, the latter including a dedicated memory structure, an adapted pipeline, bypasses, a custom address generator and special looping structures. Synthesized in CMOS technology, the ASIP stands for its better energy-flexibility tradeoff versus reference ASIC and digital signal processing Retinex implementations.

Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.

High Dynamic Range Image Display With Halo and Clipping Prevention

The dynamic range of an image is defined as the ratio between the highest and the lowest luminance level. In a high dynamic range (HDR) image, this value exceeds the capabilities of conventional display devices; as a consequence, dedicated visualization techniques are required. In particular, it is possible to process an HDR image in order to reduce its dynamic range without producing a significant change in the visual sensation experienced by the observer. In this paper, we propose a dynamic range reduction algorithm that produces high-quality results with a low computational cost and a limited number of parameters. The algorithm belongs to the category of methods based upon the Retinex theory of vision and was specifically designed in order to prevent the formation of common artifacts, such as halos around the sharp edges and clipping of the highlights, that often affect methods of this kind. After a detailed analysis of the state of the art, we shall describe the method and compare the results and performance with those of two techniques recently proposed in the literature and one commercial software.

Video Enhancement and Dynamic Range Control of HDR Sequences for Automotive Applications

CMOS video cameras with high dynamic range (HDR) output are particularly suitable for driving assistance applications, where lighting conditions can strongly vary, going from direct sunlight to dark areas in tunnels. However, common visualization devices can only handle a low dynamic range, and thus a dynamic range reduction is needed. Many algorithms have been proposed in the literature to reduce the dynamic range of still pictures. Anyway, extending the available methods to video is not straightforward, due to the peculiar nature of video data. We propose an algorithm for both reducing the dynamic range of video sequences and enhancing its appearance, thus improving visual quality and reducing temporal artifacts. We also provide an optimized version of our algorithm for a viable hardware implementation on an FPGA. The feasibility of this implementation is demonstrated by means of a case study.

Improved neural structures for image compression

The problem considered is the effective compression of image data. Compared to the many methods which allow for high compression factors (mainly based on the DCT), the proposed neural approaches offer, after a suitable training, comparable performance both in terms of perceived image quality and measured SNR. Moreover, they are able to perform in the same step the two main required operations of transformation and selection of the most significant terms, with a correspondingly smaller computational effort.<<ETX>>

Using a Recursive Rational Filter to Enhance Color Images

Portable image acquisition devices often operate in challenging outdoor environments. The quality of the acquired scenes is often low due to the low dynamics of current sensors. Moreover, these sensors are typically equipped with low-cost hardware. Hence, the image-enhancement algorithms are bounded to work in real time using limited resources and possibly require low power. We introduce a novel method to enhance the digital images acquired in critical lighting conditions, producing high-quality images for most applications. Our algorithm separates the image into illumination and reflectance, as in the ldquoRetinexrdquo theory. These two channels are separately processed since they give different contributions to the image. We propose a simple and fast operator to estimate the illumination component employing a spatially recursive rational filter. We show some results of an extensive experimental phase to show that to separately process the illumination and reflectance channels is advantageous since the image features are better exploited. A number of measures are computed to validate our choices.

Nonlinear contrast enhancement based on the Retinex approach

In this paper we present a digital image enhancement technique which relies on the application of a nonlinear operator within the Retinex approach. The basic idea of this approach is to separate the illumination and reflectance components of the image, so that by reducing the contribution of the former it is possible to effectively control the dynamic range of the latter. However, its behaviour critically depends on the quality of the illumination estimation process, so that either annoying artifacts are generated, or very complex operators have to be used, which may prevent the use of this method in several cost- and time-sensitive applications. Our method is able to provide, thanks to the use of a suitable nonlinear operator, good quality, artifacts-free images at a limited computational complexity.

VLSI implementation of a nonlinear image interpolation filter

A novel edge-preserving image interpolation algorithm is introduced. It is based on the use of a simple nonlinear filter which reconstructs sharp edges accurately and without the ringing effects which are present in other interpolation techniques. Some simulation results on one- and two-dimensional data are presented, and a possible VLSI implementation is discussed.