A PDE Method to Segment Image Linear Objects with Application to Lens Distortion Removal

In this paper, we propose a partial differential equation based method to segment image objects, which have a given parametric shape based on energy functional. The energy functional is composed of a term that detects object boundaries and a term that constrains the contour to find a shape compatible with the parametric shape. While the shape constraints guiding the PDE may be determined from object's shape statistical models, we demonstrate the proposed approach on the extraction of objects with explicit shape parameterization, such as linear image segments. Several experiments are reported on synthetic and real images to evaluate our approach. We also demonstrate the successful application of the proposed method to the problem of removing camera lens distortion, which can be significant in medium to wide-angle lenses

A PDE Method to Segment Image Linear Objects with Application to Lens Distortion Removal

In this paper, we propose a partial differential equation based method to segment image objects, which have a given parametric shape based on energy functional. The energy functional is composed of a term that detects object boundaries and a term that constrains the contour to find a shape compatible with the parametric shape. While the shape constraints guiding the PDE may be determined from object's shape statistical models, we demonstrate the proposed approach on the extraction of objects with explicit shape parameterization, such as linear image segments. Several experiments are reported on synthetic and real images to evaluate our approach. We also demonstrate the successful application of the proposed method to the problem of removing camera lens distortion, which can be significant in medium to wide-angle lenses

Electronic Letters on Computer Vision and Image Analysis 6(2):9-21, 2007 A PDE Method to Segment Image Linear Objects with Application to Lens Distortion Removal

In this paper, we propose a partial differential equation based method to segment image objects, which have a given parametric shape based on energy functional. The energy functional is composed of a term that detects object boundaries and a term that constrains the contour to find a shape compatible with the parametric shape. While the shape constraints guiding the PDE may be determined from object's shape statistical models, we demonstrate the proposed approach on the extraction of objects with explicit shape parameterization, such as linear image segments. Several experiments are reported on synthetic and real images to evaluate our approach. We also demonstrate the successful application of the proposed method to the problem of removing camera lens distortion, which can be significant in medium to wide-angle lenses

Performance analysis of wireless compressed-image transmission over DST-based OFDMA systems

Abstract Multimedia data, like images, consumes significant bandwidth when transmitted over wireless systems. Therefore, compressing transmitted images becomes crucial to reduce the required bandwidth and improve energy efficiency. This work aims to analyze the performance of transmitting wireless compressed images over a recent Discrete Sine Transform (DST)-Based Orthogonal Frequency Division Multiple Access (DST-OFDMA) system. It investigates the effectiveness of several image compression methods by determining the minimum Signal-to-Noise Ratio (SNR) required for each method to achieve error-free image recovery at the receiver. This work considers different modulation schemes including 16QAM and QPSK, as well as different subcarrier mapping schemes (localized and interleaved) over vehicular A, SUI3, and uniform channels. Nine standard compression methods are used for analyzing the performance of the DST-OFDMA system and compared it with that of the conventional Discrete Fourier Transform (DFT)-based OFDMA (DFT-OFDMA) system. The results show that the performance of DST-OFDMA outperforms that of DFT-OFDMA, especially when QPSK modulation is used. Simulation results demonstrate that the interleaved DST-OFDMA (DST-IOFDMA) system, employing the SPIHT_3D compression method and QPSK modulation (over the SUI3 channel model), achieves the lowest SNR value required for compressed image recovery, approximately 18 dB. This indicates that the SPIHT_3D compression method exhibits lower power consumption compared to other methods as well as high bandwidth efficiency

Performance analysis of wireless transmission of compressed images using DCT‐OFDMA system with different compression schemes

Abstract Transmitting images over an Orthogonal Frequency Division Multiplexing Access (OFDMA) system poses a significant challenge. The process entails sending a substantial amount of data, which consumes a significant amount of bandwidth. Consequently, compressing the transmitted image becomes essential to reduce the required bandwidth. The aim of this paper is to examine and analyse the wireless transmission of a compressed image via Discrete Cosine Transform (DCT‐OFDMA). A comparison is made with Discrete Fourier Transform (DFT‐OFDMA), across various subcarrier mapping schemes (localized and inter‐leaved), and different modulation schemes (16 Quadrature Amplitude Modulation (16QAM) and Quadrature Phase Shift Keying (QPSK)) using vehicular A, Stanford University Interim (SUI3), and uniform channel models. To evaluate the performance of the system, the minimum Signal‐to‐Noise Ratio (SNR) necessary to recover the transmitted compressed image is calculated. This work considers nine standard compression techniques. The results are carried out using the MATLAB simulator. According to the simulation results, the minimum SNR required to recover the transmitted compressed image was found to be 19 dB. This result was achieved when using Discrete Cosine Transform‐Loaclized‐Orthogonal Frequency Division Multiplexing Access (DCT‐LOFDMA) with QPSK modulation and set partitioning in hierarchical trees (SPIHT) compression method over the SUI3 channel model. Moreover, it was observed that the DCT‐LOFDMA and DFT‐IOFDMA systems attained equal SNR while utilizing the SPIHT_3D compression technique and QPSK modulation on the SUI3 channel model. Overall, the results suggest that the performance of DCT‐based localized OFDMA is somewhat superior to DFT‐based localized OFDMA, particularly when utilizing the SUI3 channel model and the QPSK modulation scheme. Therefore, it is feasible to transmit and receive a compressed image effectively over an OFDMA system with DCT