T. Frajka

Bio: T. Frajka is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Wavelet transform & Second-generation wavelet transform. The author has an hindex of 4, co-authored 6 publications receiving 96 citations.

Residual image coding for stereo image compression

Abstract: One main focus of research in stereo image coding has been disparity estimation, a technique used to reduce the coding rate by taking advantage of the redundancy in a stereo image pair. Significantly less effort has been put into the coding of the residual image. These images display characteristics that are different from that of natural images. We propose a new method for the coding of residual images that takes into account the properties of residual images. Particular attention is paid to the effects of occlusion and the correlation properties of residual images that result from block-based disparity estimation. The embedded, progressive nature of our coder enables one to stop decoding at any time. We demonstrate that it is possible to achieve good results with a computationally simple method.

Progressive image coding with spatially variable resolution

Abstract: We present a wavelet-based progressive image coding system that allows the specification of regions of interest to alter the spatial allocation of future transmitted bits. When used in an interactive mode with feedback, the viewer, after seeing a low resolution version of the image, can instruct the encoder to concentrate more effort on coding regions of interest. When operating in an independent mode, the encoder can select regions of interest based on automatic feature recognition algorithms or offline human selection. The algorithm is flexible enough to adapt to changes of interest during encoding.

Memory efficient quadtree wavelet coding for compound images

Abstract: Wavelet-based image coders generally perform well on natural images, which are typically characterized by slowly varying image intensities. Their performance suffers, however on compound images containing both text and image data. We modify a quadtree wavelet coder to perform well on text image data by treating text blocks differently from non-text blocks. We combine wavelet domain processing of non-text blocks with spatial domain processing of text blocks, and achieve improved performance over purely wavelet domain techniques for compound images.

Image compression for memory constrained printers

Abstract: We study memory efficient image compression techniques for color digital printers. Particular constraints imposed by printers are incorporated into the algorithms presented. We present a method for ordering the wavelet coefficient information in a compressed bit stream to allow a decoded image to be sequentially decompressed, from the top of an image to the bottom, as the paper exits the printer. In addition, we use a hybrid filtering scheme that uses different horizontal and vertical filters, each with different depths of wavelet decomposition.

Robust packet image transmission by wavelet coefficient dispersement

Abstract: We present a packetization method for robust image transmission over packet erasure channels. The packets are formed in such a way that the image information is spread over different frequency bands and spatial locations to avoid complete disruption of certain image blocks in case of a packet loss. Experimental results are provided to demonstrate the performance of this method.

Segmented layered image system

Abstract: Systems and methods for encoding and decoding document images are disclosed. Document images are segmented into multiple layers according to a mask. The multiple layers are non-binary. The respective layers can then be processed and compressed separately in order to achieve better compression of the document image overall. A mask is generated from a document image. The mask is generated so as to reduce an estimate of compression for the combined size of the mask and multiple layers of the document image. The mask is then employed to segment the document image into the multiple layers. The mask determines or allocates pixels of the document image into respective layers. The mask and the multiple layers are processed and encoded separately so as to improve compression of the document image overall and to improve the speed of so doing. The multiple layers are non-binary images and can, for example, comprise a foreground image and a background image.

System and method for transmitting a digital image over a communication network

Abstract: The imaging system that is described below is an image streaming system which is different from traditional compression systems. It eliminates the necessity to store a compressed version of the original image, by streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the full image. Instead, once a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI. Since the size of the ROI is bounded by the size and resolution of the viewing device at the client and not by the size of the image, only a small portion of the full progressive coding computation is performed for a local area of the original image. This local property is also true for the client. The client computer performs decoding and rendering only for ROI and not the full image. This real time streaming or Pixels-On-Demand™ architecture requires different approaches even to old ideas. For example, similarly to some prior art, the present imaging system is based on wavelets. But while in other systems wavelet bases are selected according to their coding abilities, the choice of wavelet bases in the present imaging system depends more on their ability to perform well in the real time framework. The system of the present invention supports several modes of progressive transmission: by resolution, by accuracy and by spatial order.

Stereoscopic image quality metrics and compression

Abstract: We are interested in metrics for automatically predicting the compression settings for stereoscopic images so that we can minimize file size, but still maintain an acceptable level of image quality. Initially we investigate how Peak Signal to Noise Ratio (PSNR) measures the quality of varyingly coded stereoscopic image pairs. Our results suggest that symmetric, as opposed to asymmetric stereo image compression, will produce significantly better results. However, PSNR measures of image quality are widely criticized for correlating poorly with perceived visual quality. We therefore consider computational models of the Human Visual System (HVS) and describe the design and implementation of a new stereoscopic image quality metric. This, point matches regions of high spatial frequency between the left and right views of the stereo pair and accounts for HVS sensitivity to contrast and luminance changes at regions of high spatial frequency, using Michelson's Formula and Peli's Band Limited Contrast Algorithm. To establish a baseline for comparing our new metric with PSNR we ran a trial measuring stereoscopic image encoding quality with human subjects, using the Double Stimulus Continuous Quality Scale (DSCQS) from the ITU-R BT.500-11 recommendation. The results suggest that our new metric is a better predictor of human image quality preference than PSNR and could be used to predict a threshold compression level for stereoscopic image pairs.

Gaze-contingent multiresolutional displays: an integrative review.

Abstract: Gaze-contingent multiresolutional displays (GCMRDs) center high-resolution information on the user's gaze position, matching the user's area of interest (AOI). Image resolution and details outside the AOI are reduced, lowering the requirements for processing resources and transmission bandwidth in demanding display and imaging applications. This review provides a general framework within which GCMRD research can be integrated, evaluated, and guided. GCMRDs (or "moving windows") are analyzed in terms of (a) the nature of their images (i.e., "multiresolution," "variable resolution," "space variant," or "level of detail"), and (b) the movement of the AOI (i.e., "gaze contingent," "foveated," or "eye slaved"). We also synthesize the known human factors research on GCMRDs and point out important questions for future research and development. Actual or potential applications of this research include flight, medical, and driving simulators; virtual reality; remote piloting and teleoperation; infrared and indirect vision; image transmission and retrieval; telemedicine; video teleconferencing; and artificial vision systems.

Lossy/lossless region-of-interest image coding based on set partitioning in hierarchical trees

Abstract: We have incorporated a region-of-interest (RoI) coding functionality into Said and Pearlman's (see IEEE. Trans. CSVT, vol.6, p.243-50, 1996) SPIHT coding with integer transforms. By placing a higher emphasis on the transform coefficients pertaining to the RoI, the RoI is coded with higher fidelity than the rest of the image in earlier stages of progressive reconstruction thus the "important" part of the image is reconstructed more quickly than the rest of the image. This method significantly saves transmission time and storage space by terminating encoding or transmission in situations where the RoI needs to be coded losslessly and the rest of the image visually losslessly (lossy). In our model, the RoI can be flexibly specified either in the beginning or in the middle of the encoding process (either on the original image or on the full- or low-resolution image reconstructed by the decoder), through interaction with the user at the transmitting or the receiving end. Also, the speed with which the quality of the RoI improves in progressive decoding is flexibly specified by the user at either end. The proposed method is especially advantageous in an application where the image is browsed interactively, e.g. telemedicine.