Manolis S. Sangriotis

Stereo image compression using wavelet coefficients morphology

Abstract In this paper, we propose a new stereo image compression scheme that is based on the wavelet transform of both images and the disparity estimation between the stereo pair subbands. The two images are decomposed by using a Discrete Wavelet Transform (DWT) and coded by employing the morphological representation of the wavelet coefficients, which is a technique that exploits the intraband–interband statistical properties of them. The progressive pixel-to-pixel evaluation of the disparity has been incorporated to the morphological coder so that a dense disparity field to be formed for every subband. The proposed method demonstrates very good performance as far as PSNR measures and visual quality are concerned and low complexity.

Effect of different traversal schemes in integral image coding

Integral imaging (InIm) is a highly promising technique for the delivery of three-dimensional (3D) image content. During capturing, different views of an object are recorded as an array of elemental images (EIs), which form the integral image. High-resolution InIm requires sensors with increased resolution and produces huge amounts of highly correlated data. In an efficient encoding scheme for InIm compression both inter-EI and intra-EI correlations have to be properly exploited. We present an EI traversal scheme that maximizes the performance of InIm encoders by properly rearranging EIs to increase the intra-EI correlation of jointly coded EIs. This technique can be used to augment performance of both InIm specific and properly adapted general use encoder setups, used in InIm compression. An objective quality metric is also introduced for evaluating the effects of different traversal schemes on the encoder performance.

Morphological wavelet-based stereo image coders

Abstract In this paper, we propose a family of novel stereoscopic image coders based on morphological coding and a block-based disparity compensation algorithm. The proposed schemes employ discrete wavelet transform decomposition and a morphological coder that lowers total entropy by exploiting the intra-band and inter-band statistical properties of the wavelet coefficients. This ensures high coding efficiency, embedded bit streams, fast execution, and simple implementation. Disparity compensation procedure is implemented on blocks of fixed or variable size employing the block-matching algorithm. The blocks of variable size are formed as a result of Right image’s quad-tree decomposition with a simplified rate-distortion criterion. This technique adapts block size to regions of almost constant binocular disparity in contradiction with fixed block size based disparity estimation that divides these regions into smaller blocks, thus requiring more disparity vectors. The Left and the resulting predictive error images are subsequently transformed, quantized, and coded. The wavelet nature of the algorithm and the proposed disparity compensation provide reconstructed images without blocking artifacts and fewer annoying ringing effects. The extensive experimental evaluation shows that the proposed coders demonstrate very good performance as far as PSNR measures and visual quality are concerned, as well as low complexity.

Photorealistic integral photography using a ray-traced model of capturing optics

We present a new approach for computer-generated integral photography (IP) based on ray tracing, for the reconstruction of high quality photorealistic 3-D images of increased complexity. With the proposed methodology, all the optical elements of a single-stage IP capturing setup are physically modeled for the production of real and virtual orthoscopic IP images with depth control. This approach is straightforward for translating a computer-generated 3-D scene to an IP image, and constitutes a robust methodology for developing modules that can be easily integrated in existing ray tracers. An extension of this technique enables the generation of photorealistic 3-D videos [integral videography (IV)] and provides an invaluable tool for the development of 3-D video processing algorithms.

A computer-aided system for malignancy risk assessment of nodules in thyroid US images based on boundary features

In this paper, a novel computer-based approach is proposed for malignancy risk assessment of thyroid nodules in ultrasound images. The proposed approach is based on boundary features and is motivated by the correlation which has been addressed in medical literature between nodule boundary irregularity and malignancy risk. In addition, local echogenicity variance is utilized so as to incorporate information associated with local echogenicity distribution within nodule boundary neighborhood. Such information is valuable for the discrimination of high-risk nodules with blurred boundaries from medium-risk nodules with regular boundaries. Analysis of variance is performed, indicating that each boundary feature under study provides statistically significant information for the discrimination of thyroid nodules in ultrasound images, in terms of malignancy risk. k-nearest neighbor and support vector machine classifiers are employed for the classification tasks, utilizing feature vectors derived from all combinations of features under study. The classification results are evaluated with the use of the receiver operating characteristic. It is derived that the proposed approach is capable of discriminating between medium-risk and high-risk nodules, obtaining an area under curve, which reaches 0.95.

Accurate lattice extraction in integral images

Integral imaging is one of the most promising techniques for delivering three-dimensional content. Most processing tasks usually require prior knowledge of the size and positions of the elemental images that comprise an integral image. In this paper we propose an automated method for calibrating the acquisition setup, by applying a preprocessing stage to an acquired integral image. The skew angle is extracted and the size and positions of the elemental images are accurately determined. For these purposes a method is developed to automatically identify an elemental image lattice that best matches the acquired integral image.

Stereo image coder based on the MRF model for disparity compensation

This paper presents a stereoscopic image coder based on the MRF model and MAP estimation of the disparity field. The MRF model minimizes the noise of disparity compensation, because it takes into account the residual energy, smoothness constraints on the disparity field, and the occlusion field. Disparity compensation is formulated as an MAP-MRF problem in the spatial domain, where the MRF field consists of the disparity vector and occlusion fields. The occlusion field is partitioned into three regions by an initial double-threshold setting. The MAP search is conducted in a block-based sense on one or two of the three regions, providing faster execution. The reference and residual images are decomposed by a discrete wavelet transform and the transform coefficients are encoded by employing the morphological representation of wavelet coefficients algorithm. As a result of the morphological encoding, the reference and residual images together with the disparity vector field are transmitted in partitions, lowering total entropy. The experimental evaluation of the proposed scheme on synthetic and real images shows beneficial performance over other stereoscopic coders in the literature.

Robust integral image rectification framework using perspective transformation supported by statistical line segment clustering

In most integral image analysis and processing tasks, accurate knowledge of the internal image structure is required. In this paper we present a robust framework for the accurate rectification of perspectively distorted integral images based on multiple line segment detection. The use of multiple line segments increases the overall fault tolerance of our framework providing strong statistical support for the rectification process. The proposed framework is used for the automatic rectification, metric correction, and rotation of distorted integral images. The performance of our framework is assessed over a number of integral images with varying scene complexity and noise levels.

Physical modeling of a microlens array setup for use in computer generated IP

One of the most promising techniques for visualizing three-dimensional objects is Integral Photography (IP). Two of the most common methods used in Computer Generated IP involve the development of simplified ray tracing algorithms for elementary 3D objects or the realization of pinhole arrays. We present an alternative technique based on the POV-Ray software package for ray tracing to generate synthetic, high quality and photorealistic integral images, by accurately modeling all the optical elements of the capturing setup. Our work constitutes a straightforward approach for translating a computer generated 3D model to an IP image and a robust method to develop modules that can be easily integrated in existing ray-tracers. The proposed technique simulates the procedure of a single stage IP capture for producing orthoscopic IP images, real or virtual. Full control is provided over geometry selection, size and refractive index of the elementary microlenses. Specifically our efforts have been focused on the development of arrays with different geometries (square or hexagonal) that demonstrates the parameterization capabilities of the proposed IP setup. Moreover detailed benchmarking is provided over a variety of sizes and geometries of microlens arrays.

Perspective rectification of integral images produced using arrays of circular lenses

There are many different three-dimensional (3D) techniques to capture and deliver autostereoscopic 3D content. A promising technique that provides two-dimensional parallax as well as high-quality, full-color 3D content is integral imaging (InI). Misalignments between the lens arrays (LAs) and the camera charged coupled device, however, introduce geometric distortions in the acquired image that propagate through the different image processing stages and deteriorate the 3D effect. Here, we propose a method to accurately rectify the perspective distortion of integral images (InIms) generated using circular lenses. Using an edge-linking approach, we extracted elliptically shaped contours of elemental images in the perspectively distorted InIm. To calculate the rectification matrix, we used the images of the circular points. Subsequently, we applied a triangulation scheme followed by a statistical approach to accurately estimate the grid structure of the LA. Finally, we provided experimental results over a wide range of InIms to evaluate the robustness and accuracy of the proposed method using objective metrics.