High peak to average power ration (PAPR) in orthogonal frequency division multiplexing (OFDM) is an important problem, which increase the cost and complexity of high power amplifiers. One of the techniques used to reduce the PAPR in OFDM system is the tone reservation method (TR). In our work we propose a modified tone reservation method to decrease the PAPR with low complexity compared with the conventional TR method by process the high and low amplitudes at the same time. An image of size 128×128 is used as a source of data that transmitted using OFDM system. The proposed method decrease the PAPR by 2dB compared with conventional method with keeping the performance unchanged. The performance of the proposed method is tested with

Communication is one of the vast and rapidly growing fields of engineering, where
increasing the efficiency of communication by overcoming the external
electromagnetic sources and noise is considered a challenging task. To achieve
confidentiality for color image transmission over the noisy communication channels
a proposed algorithm is presented for image encryption using AES algorithm. This
algorithm combined with error detections using Cyclic Redundancy Check (CRC) to
preserve the integrity of the encrypted data. This paper presents an error detection
method uses Cyclic Redundancy Check (CRC), the CRC value can be generated by
two methods: Serial and Parallel CRC Implementation. The proposed algorithm for
the

In this paper a new fusion method is proposed to fuse multiple satellite images that are acquired through different electromagnetic spectrum ranges to produce a single gray scale image. The proposed method based on desecrate wavelet transform using pyramid and packet bases, the fusion process preformed using two different fusion rules, where the low frequency part is remapped through the use of PCA analysis basing on covariance matrix and correlation matrix, and the high frequency part is fused using different fusion rules (adding, selecting the higher, replacement), then the restored image is obtained by applying the inverse desecrate wavelet transform. The experimental results show the validity of the proposed fusion method to fuse suc

     Digital images are open to several manipulations and dropped cost of compact  cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image  by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple

Combining multi-model images of the same scene that have different focus distances can produce clearer and sharper images with a larger depth of field. Most available image fusion algorithms are superior in results. However, they did not take into account the focus of the image. In this paper a fusion method is proposed to increase the focus of the fused image and to achieve highest quality image using the suggested focusing filter and Dual Tree-Complex Wavelet Transform. The focusing filter consist of a combination of two filters, which are Wiener filter and a sharpening filter. This filter is used before the fusion operation using Dual Tree-Complex Wavelet Transform. The common fusion rules, which are the average-fusion rule and maximu

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

The Fauqi field is located about 50Km North-East Amara town in Missan providence in Iraq. Fauqi field has 1,640 MMbbl STOIIP, which lies partly in Iran. Oil is produced from both Mishrif and Asmari zones. Geologically, the Fauqi anticline straddles the Iraqi/Iranian border and is most probably segmented by several faults. There are several reasons leading to drilling horizontal wells rather than vertical wells. The most important parameter is increasing oil recovery, particularly from thin or tight reservoir permeability. The Fauqi oil field is regarded as a giant field with approximately more than 1 billion barrels of proven reserves, but it has recently experienced low production rate problems in many of its existing wells. This study

Two prevalent neurodevelopment disorders in children are attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). The fifth version of the Diagnostic and Statistical Manual of Mental Disorders describes autism as a condition marked by limitations in social communication as well as restricted, repetitive behavior patterns. While impulsivity, hyperactivity, and lack of concentration are signs of attention deficit hyperactivity disorder. Boys experience it more frequently than girls do. This study sought for possible factors that put children at risk for autism and attention deficit hyperactivity disorder, and it investigated the association between neurodevelopment disorders in children and parental risk factor i

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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