ANOTHER LOOK AT THE RETINA AS AN IMAGE SCALAR QUANTIZER

International audienceWe investigate, in this paper, the processing of stimuli in the mammalians retina, and raise the analogy between the biological mechanisms involved and already existing analog-to-digital converters functioning. Besides, we propose a possible decoding procedure for the retina neural code under the restrictions of the model presented. The coder/decoder, we describe here, focuses on the temporal behavior of the three last retina layers. As time goes, our system gradually changes from a quasi-uniform quantizer to a highly non-linear one. Besides, high magnitude stimuli are well refined, while small magnitudes are coarsely approximated. This yields an original bioinspired quantization system, the behavior of which evolves dynamically during the time interval of stimuli observation. Here, we present a biologically realistic retina model adapted to a temporal signal. Then, we explore the input/output map of the system and its ability to recover the original signal. Further, we make the parallel between this bioinspired system and well known compandor/quantizer systems used for analog-to-digital converters. Finally, we compare the performance of our quantizer to the dead zone uniform scalar quantizer used in JPEG2000, and show a slightly better behavior for low rate transmissions

Another look at the retina as an image dithered scalar quantizer

International audienceWe explore, in this paper, the behavior of the mammalians retina considered as an analog-to-digital converter for the incoming light stimuli. This work extends our previous effort towards combining results in neurosciences with image processing techniques [1]. We base our study on a biologically realistic model that reproduces the neural code as generated by the retina. The neural code, that we consider here, consists of non-deterministic temporal sequences of uniformly shaped electrical impulses, also termed as spikes. We describe, starting from this spike-based code, a dynamic quantization scheme that relies on the so-called rate coding hypothesis. We, then, propose a possible decoding procedure. This yields an original quantizing/de-quantizing system which evolves dynamically from coarse to fine, and from uniform to non-uniform. Furthermore, we emit a possible interpretation for the non-determinism observed in the spike timings. In order to do this, we implement a three-staged processing system mapping the anatomical architecture of the retina. We, then, model the retinal noise by a dither signal which permits us to define the retina behavior as a non-subtractive dithered quantizer. The quantizing/de-quantizing system, that we propose, offers several interesting features as time scalability as well as reconstruction error whitening and de-correlation from the input stimuli

Streaming an image through the eye: The retina seen as a dithered scalable image coder

We propose the design of an original scalable image coder/decoder that is inspired from the mammalians retina. Our coder accounts for the time-dependent and also nondeterministic behavior of the actual retina. The present work brings two main contributions: As a first step, (i) we design a deterministic image coder mimicking most of the retinal processing stages and then (ii) we introduce a retinal noise in the coding process, that we model here as a dither signal, to gain interesting perceptual features. Regarding our first contribution, our main source of inspiration will be the biologically plausible model of the retina called Virtual Retina. The main novelty of this coder is to show that the time-dependent behavior of the retina cells could ensure, in an implicit way, scalability and bit allocation. Regarding our second contribution, we reconsider the inner layers of the retina. We emit a possible interpretation for the non-determinism observed by neurophysiologists in their output. For this sake, we model the retinal noise that occurs in these layers by a dither signal. The dithering process that we propose adds several interesting features to our image coder. The dither noise whitens the reconstruction error and decorrelates it from the input stimuli. Furthermore, integrating the dither noise in our coder allows a faster recognition of the fine details of the image during the decoding process. Our present paper goal is twofold. First, we aim at mimicking as closely as possible the retina for the design of a novel image coder while keeping encouraging performances. Second, we bring a new insight concerning the non-deterministic behavior of the retina.Comment: arXiv admin note: substantial text overlap with arXiv:1104.155

A bio-inspired image coder with temporal scalability

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.Comment: 12 pages; Advanced Concepts for Intelligent Vision Systems (ACIVS 2011

Map online system using internet-based image catalogue

Digital maps carry along its geodata information such as coordinate that is important in one particular topographic and thematic map. These geodatas are meaningful especially in military field. Since the maps carry along this information, its makes the size of the images is too big. The bigger size, the bigger storage is required to allocate the image file. It also can cause longer loading time. These conditions make it did not suitable to be applied in image catalogue approach via internet environment. With compression techniques, the image size can be reduced and the quality of the image is still guaranteed without much changes. This report is paying attention to one of the image compression technique using wavelet technology. Wavelet technology is much batter than any other image compression technique nowadays. As a result, the compressed images applied to a system called Map Online that used Internet-based Image Catalogue approach. This system allowed user to buy map online. User also can download the maps that had been bought besides using the searching the map. Map searching is based on several meaningful keywords. As a result, this system is expected to be used by Jabatan Ukur dan Pemetaan Malaysia (JUPEM) in order to make the organization vision is implemented

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Detectability model for the evaluation of lossy compression methods on radiographic images

The purpose of image data compression is to represent data efficiently without loss of information. This involves identification and removal of unnecessary information. Uncompressed image data is typically represented in such a way so that it is highly redundant. Need for data reduction arises due to limitation on storage space or transmission time. Although the storage capacities of magnetic media increases, the demand for data compression has been growing steadily. The Nuclear Regulatory Commission requires that the radiographs be stored for 100 years. The film radiograph degrades due to aging. To avoid this generally the radiograph is digitized between 35 and 100 micron spatial resolution and 12 bits. For a 11x14 inch radiograph this requires on the order of 30 Mbytes for storage. Data compression is necessary to increase the number of images that can be stored. Various factors used in the evaluation of compression are the amount of compression provided, speed of compression and decompression, memory requirements and the mean square error (MSE). Since the radiographs are viewed by the human eye, it is very important that the compression does not introduce any artifacts that are visible. It is necessary to evaluate the visual impact of the error due to compression. In this thesis, a method is presented which calculates the visual distortion of the compressed image as compared to the original image. This method is based on a model of the human eye