With the maturity of image editing software, image content has been forged frequently, posing potential threats to many critical fields. To detect forgery images effectively, this paper proposes an image copy-move forgery detection (CMFD) method based on speeded-up robust feature (SURF) and polar complex exponential transform (PCET). Firstly, image is divided into non-overlapping irregular image blocks by superpixel segmentation. Then, these image blocks are separated into two categories: smooth regions and texture regions. Secondly, after finding the keypoints by SURF, the PCET coefficients are extracted and utilized for searching similar features by feature matching algorithm. Thirdly, a strategy is used to eliminate false matched points and find the regions with dense matched points. It combines the random sample consensus (RANSAC) algorithm and a filtering scheme. Finally, mathematical morphology and an iterative strategy are adopted to refine the tampered regions. Compared with other CMFD methods, the proposed method can detect the forgery which occurs in high-brightness smooth regions or forgery images involving similar but genuine regions. Experimental results also indicate the proposed method can resist different distortions by various attacks, including rotation, scaling, blurring, joint photographic expert group (JPEG) compression, and noise addition.

The popularity of image editing software has made it increasingly easy to alter the content of images. These alterations threaten the authenticity and integrity of images, causing misjudgments and possibly even affecting social stability. The copy-move technique is one of the most commonly used approaches for manipulating images. As a defense, the image forensics technique has become popular for judging whether a picture has been tampered with via copy-move, splicing, or other forgery techniques. In this paper, a scheme based on accelerated-KAZE (A-KAZE) and speeded-up robust features (SURF) is proposed for image copy-move forgery detection (CMFD). It is difficult for most keypoint-based CMFD methods to obtain sufficient points in smooth regions. To remedy this defect, the response thresholds for the A-KAZE and SURF feature detection stages are set to small values in the proposed method. In addition, a new correlation coefficient map is presented, in which the duplicated regions are demarcated, combining filtering and mathematical morphology operations. Numerous experiments are conducted to demonstrate the effectiveness of the proposed method in searching for duplicated regions and its robustness against distortions and post-processing techniques, such as noise addition, rotation, scaling, image blurring, joint photographic expert group (JPEG) compression, and hybrid image manipulation. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested CMFD methods.

In this paper, an improved digital watermarking scheme combined with multi-level discrete cosine transform (DCT), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed. To improve the security of the watermark, the encrypted watermark is acquired by Arnold transform before watermark embedding. The proposed scheme is proved to be robust, and its performance is evaluated with respect to the normalized correlation (NC) and peak signal-to-noise ratio (PSNR). The robustness of the proposed scheme is also evaluated under different attacks which include salt and pepper noise, Gaussian noise, and other attacks. The experimental results are also conducted to verify the effect of false positive problem which exists in most watermarking schemes based on SVD.

An analytical model is proposed to describe the priority schemes of the enhanced distributed channel access (EDCA) mechanism of the IEEE 802.11e standard. EDCA provides class-based differentiated quality of service (QoS) to IEEE 802.11 wireless local area networks (WLANs). However, One of the main challenges with 802.11e EDCA is the configuration of the open parameters of this mechanism, namely arbitration inter frame space (AIFS), contention window (CW) and transmission opportunity (TXOP). In this paper, we focus on the optimal configuration of parameter CW in order to improve the throughput performance of the WLAN. We present an approach to set parameter CW according to channel status. Then, based on this model, we search for the optimal throughput with EDCA. Finally, we show the model is calculated numerically and validated against simulation results.

Based on a deep understanding of all-phase digital filter (APDF) design and all-phase biorthogonal transform (APBT), this paper will further study the windowed all-phase digital filter (WAPDF) and windowed all-phase biorthogonal transform (WAPBT), discuss the principle of the WAPBT, and provide a unified construction method of the all-phase transform (APT). Based on a type of orthogonal transform, i.e., discrete sine transform (DST), an interpolation filter called an all-phase DST (APDST) filter is constructed and used for image demosaicking; it is compared with bilinear interpolation and all-phase inverse discrete cosine transform (APIDCT) interpolation filters, to test its performance in image interpolation and provide analysis and discussion. The experimental results show that APIDCT and APDST filters with a size of 7 × 7 are similar in interpolation performance, but better than the bilinear interpolation method. In addition to its use in image interpolation demosaicking, the low-pass filter designed in this paper can also be widely used in image interpolation, image denoising, image resizing, and other fields of image processing.