Evaluation of a Hyperspectral Image Database for Demosaicking Purposes

International audienceWe present a study on the the applicability of hyperspectral images to evaluate color filter array (CFA) design and the performance of demosaicking algorithms. The aim is to simulate a typical digital still camera processing pipe-line and to compare two different scenarios: evaluate the performance of demosaicking algorithms applied to raw camera RGB values before color rendering to sRGB, and evaluate the performance of demosaicking algorithms applied on the final sRGB color rendered image. The second scenario is the most frequently used one in literature because CFA design and algorithms are usually tested on a set of existing images that are already rendered, such as the Kodak Photo CD set containing the well-known lighthouse image. We simulate the camera processing pipe-line with measured spectral sensitivity functions of a real camera. Modeling a Bayer CFA, we select three linear demosaicking techniques in order to perform the tests. The evaluation is done using CMSE, CPSNR, s-CIELAB and MSSIM metrics to compare demosaicking results. We find that the performance, and especially the difference between demosaicking algorithms, is indeed significant depending if the mosaicking/demosaicking is applied to camera raw values as opposed to already rendered sRGB images. We argue that evaluating the former gives a better indication how a CFA/demosaicking combination will work in practice, and that it is in the interest of the community to create a hyperspectral image dataset dedicated to that effect

A No Reference Objective Color Image Sharpness Metric

International audienceIn this work, we propose a no reference color image quality assessment metric. The proposed metric makes use of a wavelet-based multiscale structure tensor [1] as an extension of the single-scale structure tensor proposed by Di Zenzo [15]. The multiscale structure tensor allows for accumulating multiscale gradient information of local regions of the color image. Thus, averaging properties are maintained while preserving edge structure. This structure tensor is capable of identifying edges in spite of the presence of noise. Once edges are identified, we define a sharpness metric based on the eigenvalues of the multiscale structure tensor. Particularly, we show that the difference of the eigenvalues of the multiscale structure tensor can be used to measure the sharpness of color edges. Based on this fact we formulate our no reference sharpness metric for color images. Experiments performed on LIVE database indicate that the objective scores obtained by the proposed metric agree well with the subjective assessment score

CYCLOP: A stereo color image quality assessment metric

International audienceIn this work, a reduced reference (RR) perceptual quality metric for color stereoscopic images is presented. Given a reference stereo pair of images and their "distorted" version, we first compute the disparity map of both the reference and the distorted stereoscopic images. To this end, we define a method for color image disparity estimation based on the structure tensors properties and eigenvalues/eigenvectors analysis. Then, we compute the cyclopean images of both the reference and the distorted pairs. Thereafter, we apply a multispectral wavelet decomposition to the two cyclopean color images in order to describe the different channels in the human visual system (HVS). Then, contrast sensitivity function (CSF) filtering is performed to obtain the same visual sensitivity information within the original and the distorted cyclopean images. Thereafter, based on the properties of the human visual system (HVS), rational sensitivity thresholding is performed to obtain the sensitivity coefficients of the cyclopean images. Finally, RR stereo color image quality assessment (SCIQA) is performed by comparing the sensitivity coefficients of the cyclopean images and studying the coherence between the disparity maps of the reference and the distorted pairs. Experiments performed on color stereoscopic images indicate that the objective scores obtained by the proposed metric agree well with the subjective assessment scores

Spatial-temporal video quality metric based on an estimation of QoE

International audienceIn this work a new Reduced Reference (RR) Video Quality Metric (VQM) is proposed. The method takes advantage of the Human Visual System (HVS) sensitivity to sharp changes in the video. In the first step, the matching regions are calculated using a temporal approach. The quality of these regions are then evaluated using a spatial approach in the last step the quality of the video is calculated based on the parameters gathered in the spatial and temporal domain. An important improvement lies in taking into account the Quality of Experience (QoE) represented as the motion activity density of the reference video. Due to the spatial-temporal approach taken, the metric is named STAQ (Spatial-Temporal Assessment of Quality). The results show a great improvement in the case of H.264 and MPEG-2 compressed and IP distorted videos even when compared to state of the art Full Reference (FR) metrics

Camera motion influence on dynamic saliency central bias

International audienceSaliency models have been extensively studied for static images and the focus is now on moving images. There is a central bias in both cases that is emphasized in the dynamic case. One aspect in this latter is the camera motion that influences the scene interpretation. The movie director exploits this motion to make the observer focus on the targeted object which is often in the center of the scene. This aspect is not taken into account in current saliency dynamic models. In this paper, we study the camera motion influence on the gaze distribution in order to include it in a new saliency model. Observers' gazes are recorded with an eye tracker, camera motions (e.g. tracking, zoom...) are calculated thanks to a polynomial projection of the motion field and the motion influence is statistically tested on the recorded gazes

Point-Based Proxy and Interactive HDR Rendering From Unstructured Photographs

This paper presents a new image-based rendering method, based on photographs acquired with handheld cameras whose characteristics are unknown. Our system relies on recent calibration advances that use robust shape descriptors such as SIFT or SURF, associated with matching methods, producing a cloud of 3D points that belongs to the surface of acquired objects. The proposed method provides an interactive navigation system, with a high refresh rate, without any polygonal geometric reconstruction of objects. For a new viewpoint, our method performs the following operations: (i) point cloud projection onto the camera, (ii) depth interpolation in image space, (iii) reverse projection of input photographs to estimate the value of each pixel in the new view, (iv) occlusions management system for avoiding re-projection errors depending on the view. With this system, high dynamic range images can also be produced from freehand shooting

A JPEG-Like Algorithm for Compression of Single-Sensor Camera Image

International audienceThis paper presents a JPEG-like coder for image compression of single-sensor camera images using a Bayer Color Filter Array (CFA). The originality of the method is a joint scheme of compression.demosaicking in the DCT domain. In this method, the captured CFA raw data is first separated in four distinct components and then converted to YCbCr. A JPEG compression scheme is then applied. At the decoding level, the bitstream is decompressed until reaching the DCT coefficients. These latter are used for the interpolation stage. The obtained results are better than those obtained by the conventional JPEG in terms of CPSNR, DeltaE2000 and SSIM. The obtained JPEG-like scheme is also less complex

A Reduced-Reference Metric Based on the Interest Points in Color Images

28th Picture Coding Symposium (PCS 2010)In the last decade, an important research effort has been dedicated to quality assessment from the subjective and the objective points of view. The focus was mainly on Full Reference (FR) metrics because of the ability to compare to an original. Only few works were oriented to Reduced Reference (RR) or No Reference (NR) metrics, very useful for applications where the original image is not available such as transmission or monitoring. In this work, we propose an RR metric based on two concepts, the interest points of the image and the objects saliency on color images. This metric needs a very low amount of data (lower than 8 bytes) to be able to compute the quality scores. The results show a high correlation between the metric scores and the human judgement and a better quality range than well-known metrics like PSNR or SSIM. Finally, interest points have shown that they can predict the quality of color images

Improving the quality of H.264/AVC by using a new Rate-Quantization model

International audienceRate control plays a key role in video coding standards. Its goal is to achieve a good quality at a given target bit-rate. In H.264/AVC, rate control algorithm for both Intra and Inter-frames suffers from some defects. In the Intra-frame rate control, the initial quantization parameter (QP) is mainly adjusted according to a global target bit-rate and length of GOP. This determination is inappropriate and generates errors in the whole of video sequence. For Inter coding unit (Frame or Macroblock), the use of MAD (Mean Average Differences) as a complexity measure, remains inefficient, resulting in improper QP values because the MAD handles locally images characteristics. QP miscalculations may also result from the linear prediction model which assumes similar complexity from coding unit to another. To overcome these defects, we propose in this paper, a new Rate-Quantization (R-Q) model resulting from extensive experiments. This latter is divided into two models. The first one is an Intra R-Q model used to determine an optimal initial quantization parameter for Intra-frames. The second one is an Inter R-Q model that aims at determining the QP of Inter coding unit according to the statistics of the previous coded ones. It does not use any complexity measure and substitutes both linear and quadratic models used in H.264/AVC rate controller. Objective and subjective simulations have been carried out using JM15.0 reference software. Compared to this latter, the global R-Q model (Intra and Inter models combined) improves the coding efficiency in terms of PSNR, objectively (up to +2.01dB), subjectively (by psychophysical experiments) and in terms of computational complexity

Maximisation Perceptuelle de la Qualité de Transmission JPWL via un Canal MIMO Réaliste

National audienceThis paper proposes a global approach of JPWL (ISO/IEC 15444-11) image transmission over a realistic wireless channel able to ensure the best Quality of Service. In order to exploit the channel diversity, we consider a Closed-Loop MIMO-OFDM scheme with different precoder designs. In particular, the high flexibility of QoS precoder allows taking into account the scalability of JPWL jointly with the instantaneous MIMO channel status. This increases the visual quality of received images. The quality monitoring is made by a reduced-reference metric based on objects' saliency and interest points, both linked to human perception. It is performed in association with a robust JPWL decoder to determine the optimal decoding configuration in terms of PSNR. The proposed scheme provides very good results and its performance is shown through a realistic wireless channel