Tomislav Kartalov

An adaptive POCS algorithm for compression artifacts removal

An effective compression artifacts removal algorithm is proposed based on the theory of projections onto convex sets (POCS). It includes a block classification procedure, a ringing detection procedure, prediction of the spatial distribution of the quantization errors and estimation of the visibility of the compression artifacts. Information gained from both the spatial and transform domains, is incorporated into adaptive projections. Experiments performed on JPEG-compressed images, demonstrate the effectiveness of the proposed algorithm in suppressing both blocking and ringing artifacts, as well as the ability of the algorithm to preserve the image sharpness.

Fully automated exposure fusion algorithm for mobile platforms

In this paper, an automated algorithm for fusion of differently exposed images is proposed. The algorithm is based on Gaussian/Laplacian pyramid decomposition of the input images. It includes optimization of the pyramid height for best quality results, and decision module for the necessity of the procedure for the recorded scene. The end-user involvement in the process of the creation of the output image is completely eliminated, making this algorithm a good choice for use on a mobile platform, as add-on software for low price mobile cameras. Experimental results show high efficiency of the algorithm and excellent visual quality of the resulting images.

A real time algorithm for exposure fusion of digital images

A real time algorithm for fusion of differently exposed images is proposed in this paper. The algorithm blends the details from two images of high dynamic range scene, acquired with different exposure values, into one output image which can be displayed on low dynamic range devices. The blending is performed in the spatial domain, using pixel by pixel approach, thus eliminating the need for expensive block processing or transform domain coding. The proposed scheme works both on grey and color images. The algorithm shows high efficiency, which make it applicable on low processing power platforms, such as mobile devices. The obtained results are visually comparable with previously published algorithms that are computationally much more expensive.

No-reference image visual quality assessment using nonlinear regression

In this paper, a novel no-reference image visual quality metric is proposed based on fusion of statistical and human visual system based metrics using ε-Support Vector Regression. Different order polynomial regression was also examined as an approximation that has lower computational complexity. Compared to existing image quality assessment metrics, the proposed fused metric is able to better quantify the image quality regardless of the type of degradation. We furthermore improve the image quality assessment by training a separate regression model for each degradation type. The latter degradation specific approach yields near perfect correlation with subjective scores, however, it relies on prior knowledge of the degradation process.

A real time global motion compensation for multi-exposure imaging algorithms

The paper presents a global motion compensation algorithm, designed to work in real time on low memory and low processing power hardware platforms, such as mobile phones. The algorithm is designed as one of the parts of a fully automated exposure fusion algorithm also intended for mobile platform. It implements translational shifts to one or both of the input images (the overexposed and the underexposed) in order to achieve their spatial alignment. Although the rotational and perspective movements are not included because of the high computational load for their estimation, the experimental results show that the implementation of this algorithm yields high visual quality to the fused results in most of the practical cases.

Blocking effect reduction in low bitrate video on a mobile platform

The paper presents a new algorithm for blocking artifacts reduction in low bit rate video. The algorithm addresses the blocking effect on block boundaries, as well as the one inside the blocks. The algorithm works with variety of coding schemes, and does not exploit any information from the coded bitstream. It has extremely low complexity and it is designed to work on a mobile platform in real time. It incorporates two parts: artifacts detection procedure, which decides whether the processing is required for the particular location in the video frame, and artifacts reduction procedure, which performs the actual filtering depending on local image characteristics. The experiments confirm the algorithms effectiveness, as well as its low computational complexity.

An adaptive deblocking algorithm for low bit-rate video

The paper presents an effective and fast postprocessing technique for blocking artifacts removal in low bit-rate video. The technique utilizes one-dimensional filtering based on the characteristics of the decoded video, without any knowledge about the coding parameters. In the first phase it performs detection of presence of the blocking artifacts, while in the second phase adaptive directional filtering is applied. The procedure includes estimation of spatial activity and prediction of the spatial distribution of the quantization errors. Experiments performed on MPEG-compressed low bit-rate video demonstrate the effectiveness of the proposed algorithm in suppressing blocking artifacts and the ability of the algorithm to preserve the image sharpness.

Dynamic optimization of quality of service in cellular multi-class networks using variable number of guard channels

In this paper we propose a novel strategy for channel allocation in multi-class mobile networks with prioritized handovers, which uses dynamically variable guard channels to improve network utilization under given quality of service (QoS) constraints. We define user classes, each of them with different utilization of network channels. We consider the guard channel policy where certain number of channels is dedicated to handover calls, and also, the policy in which this number of channels is dynamically adapted to the network requirements. Our target is to obtain the influence of this methodology over performance parameters, such as call blocking and call dropping probability. Traffic, network and mobility parameters are also taken into account, such as cell capacity, traffic intensity, as well as number and distribution of subscribers per classes.

Using reduced motion vector set for real time motion registration in HDR imaging

In this paper, we propose a new global motion registration algorithm based on hierarchical motion estimation of a reduced motion vector set, specifically adapted for the properties of the HDR input images, and designed for implementation on handheld devices, demanding low computational complexity and memory load. The procedure is fully automatic and does not require any end-user involvement. The algorithm shows great effectiveness, correctly registering over 95% of the HDR input images captured by free hand.

High quality exposure fusion for mobile platforms

In this paper, a new approach for high quality automated exposure fusion on mobile or handheld devices is presented. A utilization of the devices viewfinder screen video feed data is proposed, in order to increase the overall performance of the exposure fusion, both in static scenes and in scenes with moving objects. The introduced novelties are computationally inexpensive, since the preview video is of low frame resolution. The proposed extensions are embedded to an existing exposure fusion algorithm, and the performed experimental tests show that the new extended algorithm is better than its predecessor, both visually and in terms of objective quality measures.