Alain Hore

Image Quality Metrics: PSNR vs. SSIM

In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a simple mathematical relationship between them which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and jpeg2000 compression. A series of tests realized on images extracted from the Kodak database gives a better understanding of the similarity and difference between the SSIM and the PSNR.

An Edge-Sensing Generic Demosaicing Algorithm With Application to Image Resampling

In this paper, we introduce a new demosaicing algorithm that can be used for various sensor images captured by digital cameras equipped with various red-green-blue color filter arrays. Our algorithm enhances the universal demosaicing algorithm of Lukac et al by defining a new spectral interpolation model that exploits not only the information on the color of pixels but also the relative distance between neighboring pixels within an image. Moreover, we include an edge-detection model that makes our algorithm adaptive and reduces the presence of color shifts and artifacts. A series of tests has been made on images of the Kodak database, and our algorithm performs better than the universal demosaicing algorithm with regard to both subjective and objective evaluation. The versatility of our demosaicing algorithm is also highlighted through an application to the issue of color image resampling, and we obtain conclusive experimental results.

A statistical derivation of an automatic tone mapping algorithm for wide dynamic range display

In this paper, we present a modified tone mapping algorithm for displaying wide dynamic range images with good brightness. Our algorithm embeds an automatic computation of the key parameter controlling the brightness of tone mapped images, which make use of statistical analysis of WDR images. This enables to prevent unnecessary or cumbersome manual tuning of parameters as often found in tone mapping algorithms. Experimental results performed on different WDR images show that we are able to get images which are visually pleasant and which have good brightness and contrast. The good performance of our algorithm is also confirmed numerically through the use of the tone mapping quality index (TMQI), an objective image quality measure.

An FPGA implementation of a tone mapping algorithm with a halo-reducing filter

In this paper, we present a real-time hardware implementation of an exponent-based tone mapping algorithm of Horé et al., that uses both local and global image information for improving the contrast and increasing the brightness of tone-mapped images. Although there are several tone mapping algorithms available in the literature, most of them require manual tuning of their rendering parameters. However, in our implementation, the algorithm has an embedded automatic key parameter estimation block that controls the brightness of the tone-mapped images. We also present the implementation of a Gaussian-based halo-reducing filter. The hardware implementation is described in Verilog and synthesized for a field programmable gate array device. Experimental results performed on different wide dynamic range images show that we are able to get images which are of good visual quality and have good brightness and contrast. The good performance of our hardware architecture is also confirmed quantitatively with the high peak signal-to-noise ratio and structural similarity index.

A New Filter for Reducing HALO Artifacts in Tone Mapped Images

In this paper, we present a modified hybrid global and local tone mapping algorithm for displaying wide dynamic range (WDR) images with reduced halo artifacts. Since halo artifacts are commonly found in local tone mapping algorithms, which may produce false edges or false patterns when performing edge detection or pattern recognition algorithms on the generated tone mapped images, we propose a new Gaussian-based filter for reducing these halo artifacts. Experimental results performed on different WDR images show that we are able to get images which are visually pleasant.

Hardware implementation of a real-time tone mapping algorithm based on a mantissa-exponent representation

This paper presents a hardware implementation of a mantissa/exponent-based tone mapping algorithm for wide dynamic range (WDR) images. The algorithm performs tone mapping by using a global compression model for the pixel intensities combined with a local contrast enhancement model. The pixel intensities of the WDR images used in this paper are represented in a mantissa/exponent format produced by an innovative WDR imager which takes advantage of a multi-reset technique during the capture process. The algorithm has been implemented on FPGA and designed to be very small, fast, power-efficient and has the potential to be directly integrated into the same chip as the imager. Experimental results performed by using different images show that our implementation is reliable and efficient.

Multi-Scale histogram tone mapping algorithm enables better object detection in wide dynamic range images

In this paper, we present a novel tone mapping algorithm based on multi-scale histograms and fusion (MS-Hist), for displaying wide dynamic range (WDR) images and better detection of objects such as human faces. The proposed algorithm tone maps pixels based on multiple scale local histograms, where small scales are used to preserve local contrast and large scales allow to maintain the global brightness consistency. A database of WDR images of humans depicted in high-contrast light conditions was created to validate and compare the performance of various algorithms for face detection in tasks such as biometric based identification. Our experimental results show that the proposed MS-Hist algorithm preserves image detail, brightness and high local contrast, and can benefit tasks such as face detection in WDR images.

On the design of optimal 2D filters for efficient hardware implementations of image processing algorithms by using power-of-two terms

In this paper, we present a general approximation for 2D filters by using only power-of-two terms. This enables to easily implement these filters in electronic devices such as FPGA and ASIC just by using simple hardware shifters and adders/subtractors. Consequently, no division and no multiplication operators are required, which can reduce the memory and the power needed for computing operations such as convolution. Instead of using only additions and power-of-two terms for representing a number like in the standard binary decomposition, our model also uses subtractions for representing and approximating numbers. In addition, we propose a binary tree structure for computing a minimal representation in power-of-two terms in such a way that hardware shifters used for performing a convolution with a low-pass filter for example are well reduced to their minimum. Based on some experiments performed for contrast enhancement, which is a common image processing operation, we have noticed that good results can be obtained using our approximation in terms of image quality, hardware resources, and power consumption when compared to some other binary representations.