# IET Image Processing

## Filter Results

Displaying Results 1 - 25 of 25
• ### Fast and accurate compressed sensing model in magnetic resonance imaging with median filter and split Bregman method

Publication Year: 2019, Page(s):1 - 8
| | PDF (3986 KB)

Magnetic resonance (MR) images have great importance to assist doctors in diagnosing diseases, however, the long MR images scan duration remains the primary obstacle in clinical medicine. Compressed sensing reconstructed technique in MR imaging (CS-MRI) makes it possible to reconstruct a faithful MR image from very few measurements data, which helps to reduce the scan time. The purpose of this stu... View full abstract»

• ### Dynamic texture classification using Gumbel mixtures in the complex wavelet domain

Publication Year: 2019, Page(s):9 - 14
| | PDF (2124 KB)

Dynamic texture (DT) classification has attracted extensive attention in the field of image sequence analysis. The probability distribution model, which has been used to analysis DT, can describe well the distribution property of signals. Here, the authors introduce the finite mixtures of Gumbel distributions (MoGD) and the corresponding parameter estimation method based on expectation-maximisatio... View full abstract»

• ### Efficient edge-preserved sonar image enhancement method based on CVT for object recognition

Publication Year: 2019, Page(s):15 - 23
| | PDF (3657 KB)

In the field of computer-aided recognition, edge feature is one of the key factors to determine recognition performance. Comparing to an optical image, since sonar image via acoustic wave is easily influenced by underwater environments such as particle density, temperature, and current, edge information should be boosted. Some image preprocessing techniques based on transform domain such as wavele... View full abstract»

• ### Controversial ‘pixel’ prior rule for JPEG adaptive steganography

Publication Year: 2019, Page(s):24 - 33
| | PDF (3560 KB)

Currently, the most successful model for image adaptive steganography is the framework of minimal distortion, in which a reasonable definition of costs can improve the security level. In the authors' previous work, they developed a rule for cost reassignment in spatial domain called the controversial pixel prior (CPP)' rule, which defines controversial pixels by utilizing the controversies among ... View full abstract»

• ### Machine learning-based H.264/AVC to HEVC transcoding via motion information reuse and coding mode similarity analysis

Publication Year: 2019, Page(s):34 - 43
| | PDF (3581 KB)

High-efficiency video coding (HEVC), which is the latest video coding standard, is expected to have a dominant position in the market in the near future. However, most video resources are now encoded using the H.264/AVC standard. Consequently, there is a growing need for fast H.264/AVC to HEVC transcoders to facilitate the migration to the updated standard. This paper proposes a fast H.264/AVC to ... View full abstract»

• ### DCF with high-speed spatial constraint

Publication Year: 2019, Page(s):44 - 48
| | PDF (4264 KB)

Spatially regularised discriminative correlation filters (SRDCFs) introduce spatial regularisation weights to mitigate the boundary effects caused by circular convolution which obtains superior performance. However, spatial regularisation is computationally expensive; this limits the real-time performance of SRDCF. This study proposes high-speed spatial constraint to DCFs (HSCDCFs) for tracking. U... View full abstract»

• ### Linearly uncorrelated principal component and deep convolutional image deblurring for natural images

Publication Year: 2019, Page(s):49 - 56
| | PDF (4150 KB)

Blind image deblurring of natural images still remains a demanding task. The traditional methods, pre-processes the uniform and non-uniform images with a deblurring algorithm and employs a low-rank prior algorithm. The rich textures do not possess enough similar patches in the deblurring process and this loss results in noisy images. Also, computational efficiency gets compromised during the perfo... View full abstract»

• ### Affine invariant fusion feature extraction based on geometry descriptor and BIT for object recognition

Publication Year: 2019, Page(s):57 - 72
| | PDF (6255 KB)

It is difficult to recognise an image with affine transformation due to viewing angle and distance variations. Therefore, affine invariant feature extraction is a valuable technology in the field of image recognition. Inspired by bio-visual mechanism, an affine invariant for object recognition method based on a fusion feature framework is proposed in this study, which employs geometry descriptor a... View full abstract»

• ### Computer aided diagnosis of glaucoma using discrete and empirical wavelet transform from fundus images

Publication Year: 2019, Page(s):73 - 82
| | PDF (5299 KB)

Glaucoma is a class of eye disorder; it causes progressive deterioration of optic nerve fibres. Discrete wavelet transforms (DWTs) and empirical wavelet transforms (EWTs) are widely used methods in the literature for feature extraction using image decomposition. However, to increase the accuracy for measuring features of images a hybrid and concatenation approach has been presented in the proposed... View full abstract»

• ### CT and MRI image fusion based on multiscale decomposition method and hybrid approach

Publication Year: 2019, Page(s):83 - 88
| | PDF (3138 KB)

In the fusion process of medical computed tomography (CT) and magnetic resonance image (MRI), traditional multiscale methods often reduce the contrast of fused images. Although sparse representation (SR) methods overcome this shortcoming, they are often too smooth along the strong edges of the fusion image. To overcome these shortcomings, CT and MRI image fusion based on multiscale decomposition m... View full abstract»

• ### Accommodative extractor for QIM-based watermarking schemes

Publication Year: 2019, Page(s):89 - 97
| | PDF (3060 KB)

In quantisation index modulation-based watermarking methods, each host coefficient is replaced by an adequate quantiser according to the embedded bit. However, after the attack, the distribution of the hosts does not remain the same, resulting in a failure to map coefficients to their correct bits. To maintain a good quality, many authors focused on improving the extraction, rather than playing on... View full abstract»

• ### As-global-as-possible stereo matching with adaptive smoothness prior

Publication Year: 2019, Page(s):98 - 107
| | PDF (8394 KB)

More global matching (MGM) overcomes the limitation of one-dimensional scanline optimisation in semi-global matching (SGM). Nevertheless, the possible weaknesses of the MGM algorithm are as follows: (i) onlytwodirections are considered for each image traversal direction, which may lead to massive mismatches; (ii) disparity estimation around the object boundaries usually performs terrible si... View full abstract»

• ### Fractional crow search-based support vector neural network for patient classification and severity analysis of tuberculosis

Publication Year: 2019, Page(s):108 - 117
| | PDF (4242 KB)

The world is chasing towards the automation in the severity analysis and classification of the patients based on the severity of tuberculosis (TB). The automatic classification is very much useful for developing countries that are struggling to reduce the fatality rate of the persons suffering from TB as it is a top standing infectious disease. Thus, the automatic classification of the TB patients... View full abstract»

• ### Exact Legendre–Fourier moments in improved polar pixels configuration for image analysis

Publication Year: 2019, Page(s):118 - 124
| | PDF (4001 KB)

This study presents the exact Legendre-Fourier moments and a novel arrangement of polar pixels that allows calculating orthogonal moments defined in a unit radius more accurately than traditional methods. This arrangement simplifies implementation and preserves the values of the pixels of the image during the calculation of the moments. Moreover, the exact Legendre-Fourier moments use the weighted... View full abstract»

• ### Novel image encryption algorithm based on improved logistic map

Publication Year: 2019, Page(s):125 - 134
| | PDF (7994 KB)

Chaotic mapping has been widely used in image encryption given the unpredictability, ergodicity, and sensitivity of parameters and initial values and the high correspondence with cryptography. The logistic map has the disadvantages of uneven distribution, low security, and small parameter space. In order to overcome these disadvantages, in this article, a new chaotic map based on a real-time varia... View full abstract»

• ### Mixture separability loss in a deep convolutional network for image classification

Publication Year: 2019, Page(s):135 - 141
| | PDF (2699 KB)

In machine learning, the cost function is crucial because it measures how good or bad a system is. In image classification, well-known networks only consider modifying the network structures and applying cross-entropy loss at the end of the network. However, using only cross-entropy loss causes a network to stop updating weights when all training images are correctly classified. This is the proble... View full abstract»

• ### Adaptive appearance separation for interactive image segmentation based on Dense CRF

Publication Year: 2019, Page(s):142 - 151
| | PDF (4320 KB)

Interactive segmentation has recently become a hot topic for its wide application. The authors propose an efficacious appearance separation model for interactive binary segmentation, which incorporates the difference of foreground and background colour models and the difference of corresponding geodesic models into the popular densely connected conditional random field (Dense CRF) framework. The p... View full abstract»

• ### Image deformation based on contour using moving integral least squares

Publication Year: 2019, Page(s):152 - 160
| | PDF (4048 KB)

Many effective image deformation methods have been proposed in recent years, but few of them use the contours of objects as the reference of deformation. However, the contour is an important factor, and contour-based deformation can guarantee that the edge of the object after deformation is smoother compared to point-based image deformation. This article presents an image deformation method based ... View full abstract»

• ### Development of a global batch clustering with gradient descent and initial parameters in colour image classification

Publication Year: 2019, Page(s):161 - 174
| | PDF (4528 KB)

This study addresses two issues from batch clustering usingK-means algorithm in colour image classification application. One of the major issues is the drifting phenomenon in the batch clustering due to the stochastic nature of the clustering procedure. Also in literature, the initial parameter is important to direct the clustering algorithm converge to the proper local solution. In this st... View full abstract»

• ### Reliability verification-based convolutional neural networks for object tracking

Publication Year: 2019, Page(s):175 - 185
| | PDF (5987 KB)

The authors propose a tracking algorithm based on the reliability analysis of the convolutional neural network to avoid drift. In general, most tracking algorithms implemented with the deep network consist of a single network; they obtain the tracking results according to the confidence and perform updates with the samples, which are collected based on the previous target state. However, this kind... View full abstract»

• ### Image segmentation framework based on optimal multi-method fusion

Publication Year: 2019, Page(s):186 - 195
| | PDF (6789 KB)

This study presents a multi-method fusion and optimisation framework that can optimally combine different existing methods to further enhance the segmentation performance. The framework, in which the original accumulating process is improved and a new combination process is added, is the extension of the previously developed accumulated local fuzzy c-means with spatial information' method. In the... View full abstract»

• ### Semantic convex matrix factorisation for cross-media retrieval

Publication Year: 2019, Page(s):196 - 205
| | PDF (4325 KB)

When utilising matrix factorisation to extract latent features for cross-media retrieval, semantic information may be lost in the process of factorisation. In addition, many presented approaches directly mapped different modalities into an isomorphic semantic space to conduct the similarity measurement of different modalities, which also resulted in the loss of crucial information. To address thes... View full abstract»

• ### Despeckling of ultrasound images using directionally decimated wavelet packets with adaptive clustering

Publication Year: 2019, Page(s):206 - 215
| | PDF (2347 KB)

Two-dimensional transforms are extensively used for speckle noise reduction (despeckling) in ultrasound images. This work proposes a double filter bank structure consisting of a discrete wavelet packet transform (DWPT) and directional filter bank (DFB) along with a fuzzy-based clustering technique to despeckle ultrasound images. Wavelet packet transform can efficiently reject noises based on grey ... View full abstract»

• ### Detail-enhanced target segmentation method for thermal video sequences based on spatiotemporal parameter update technique

Publication Year: 2019, Page(s):216 - 223
| | PDF (3132 KB)

Thermal images have been widely used for detection, tracking, and classification of targets at night for military purpose. A thermal imaging sensor receives the radiation energy from the target and the background, so it has advantages in night vision. However, the thermal images have lower spatial resolution and more blurred edges than colour images, and edges can be contaminated by flames. Theref... View full abstract»

• ### Structural pattern-based approach for Betacam dropout detection in degraded archived media

Publication Year: 2019, Page(s):224 - 232
| | PDF (4847 KB)

Detection of Betacam dropout defects that can occur in the digitisation process of old archived media has importance in the restoration of degraded data to a higher quality. Most of the existing methods rely on the temporal information of multiple consecutive frames to detect Betacam dropouts, which sometimes may not work well as several successive frames may contain a Betacam error at the same po... View full abstract»

## Aims & Scope

The range of topics covered by IET Image Processing includes areas related to the generation, processing and communication of visual information.

Full Aims & Scope

## Meet Our Editors

Publisher
IET Research Journals
iet_ipr@theiet.org