IET Image Processing

Image denoising is still a challenging problem in image processing. The authors propose a novel image denoising method based on a deep convolution neural network (DCNN). Different from other learning-based methods, the authors design a DCNN to achieve the noise image. Thus, the latent clear image can be achieved by separating the noise image from the contaminated image. At the training stage, the ... View full abstract»

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»

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»

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»

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»

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»

This study presents a new fully automated, fast, and accurate brain tumour segmentation method which automatically detects and extracts whole tumours from 3D-MRI. The proposed method is based on a hybrid approach that relies on a brain symmetry analysis method and a combining region-based and boundary-based segmentation methods. The segmentation process consists of three main stages. In the first ... View full abstract»

The aim of this study is watermarking image encryption based on the fractional Mellin transform (FrMT) and singular value decomposition (SVD) using deterministic phase masks (DPMs). DPMs are used in the input as well as in the frequency planes of double random phase encoding. The use of DPM structured phase mask provides an advantage of extra encryption parameters, besides overcoming the problem o... View full abstract»

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»

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»

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»

The main task of image segmentation is to partition an image into disjoint sets of pixels called clusters. Spectral clustering algorithm has been developed rapidly in recent years and it has been widely used in image segmentation. The traditional spectral clustering algorithm requires huge amount of computation to process colour images with high resolution. While one possible solution is reducing ... View full abstract»

Traditional image stitch methods based on feature point detection require long registration time for high resolution images. In the SIFT (scale invariant feature transform) algorithm, it builds difference-of-Gaussian by a linear Gauss expansion filter to obtain the feature. SIFT has poor real time. In this study, a novel image registration method based on image block is proposed to make a rough ma... View full abstract»

Quick response (QR) code, one of the two-dimensional barcodes, is now being widely used in all fields. The effectiveness of decoding, however, needs to be improved in real-time application. In most cases, the decoding procedure is time consuming, in which the detection of QR code plays an essential part. Therefore, this study proposes a fast detection method of QR code based on run-length coding: ... View full abstract»

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»

In this study, by using the quaternion algebra, multiple-parameter fractional quaternion Fourier transform (MPFrQFT) is proposed to generalise the conventional multiple-parameter fractional Fourier transform (MPFrFT) to quaternion signal processing in a holistic manner. First, the new transform MPFrQFT and its inverse transform are defined. An efficient discrete implementation method of MPFrQFT is... View full abstract»

Visual-based technologies are very useful and meaningful to driver's fatigue detection. In this study, the authors present a multi-task hierarchical CNN scheme for fatigue detection system and propose a convolutional neural network (CNN) model with multi-scale pooling (MSP-Net). `Multi-task' includes three tasks: face detection, eye and mouth state detection and fatigue detection. First, they use ... View full abstract»

With a soaring increase in the application of video surveillance in daily life, the estimation of crowd density has already become a hot field. Crowd counting has a very close relationship with traffic planning, pedestrian analysing and emergency warning. Here, a novel crowd counting method based on multi-scales head detection is proposed. The authors' approach first uses gradients difference to e... View full abstract»

As the years passed by, computers became more powerful and automation became the need of generation. Humans tried to automate their work and replace themselves with machines. This effort of transition from manual to automatic gave rise to various research fields, and document character recognition is one such field. From the last few years, there is a sincere contribution from researchers for the ... View full abstract»

Transmission of medical images among remote places is a general practice in telemedicine. Medical images may be modified intentionally or accidentally as the transmission of these may take place through unsecure networks such as internet. Before making any diagnostic decisions, the medical practitioner has to verify the integrity of region of interest (ROI) in the received medical image in order t... View full abstract»

This study introduces an image denoising method in the presence of combined speckle and Gaussian noise. The dual-tree complex wavelet transform is applied to the image in order to obtain specific coefficients characterising these types of noise. Then, these extracted coefficients are removed by thresholding and an inverse wavelet transform is applied in order to obtain the reconstructed image. A c... View full abstract»

In this study, the problem of detecting if an image has tampered is inquired; especially, the attention has been paid to the case in which the portion of an image is copied and then pasted onto another region to create a duplication or to hide some important portion of the image. The proposed copy-move forgery detection system is based on the scale-invariant feature transform (SIFT) features extra... View full abstract»

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»

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»

The authors propose an automatic method for extracting objects with fine quality from photographs. The authors' method starts with finding bounding boxes that enclose potential objects, which is achievable by state-of-the-art object proposal methods. To further segment objects within obtained bounding boxes, the authors propose a new multi-pass level-set method based on saliency detection and fore... View full abstract»