Yazar "Akman, Ali" seçeneğine göre listele

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    Architectural Design of a Fast Search Algorithm and Implementation to Intra-Mode Decision Block of Still Image Coding
    (World Scientific Publ Co Pte Ltd, 2022) Çekli, Serap; Akman, Ali
    As a requirement of many modern image compression standards faced today, a computational complexity is observed due to the best mode selection in the intra-prediction stage. This computational complexity is tried to be reduced by various techniques without affecting the performance criteria of the image. In this study, a fast search algorithm, which simplifies the mode selection process of the intra-prediction algorithm and provides calculation with less number of modes is proposed. The hardware architecture of this proposed algorithm is implemented for realization. There are two main sections of the intra-prediction algorithm in image compression, namely the image prediction process and the mode selection process. In this study, main objective is to reduce the process time of the mode selection and the simplification of the hardware design. Sum of absolute difference (SAD) is a frequently used criterion to simplify hardware design. The algorithm searches for the most suitable mode in a single step, where the decision is based on the SAD criterion preferred for the simplicity. The proposed algorithm and related hardware architecture is tested by using various experiments. The number of the modes calculated is reduced effectively, while the process is kept within the acceptable limits in terms of peak signal to noise ratio (PSNR) and compression rate (CR) performance criteria. Therefore, the number of clock cycles observed is considerably reduced. The designed architecture is synthesized for the field programmable gate arrays (FPGA) board and the obtained results are given. In addition, these results are compared with the HM reference software where the corresponding results are in accordance with the reference software.
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    Compression of Medical Images With HEVC Intra Prediction Coding
    (IEEE, 2017) Akman, Ali; Cekli, Serap
    HEVC which is the new image coding standard provides higher compression performance over the existing standards. In this study, compression of medical images is fulfilled with HEVC intra prediction method. The compressed images for storage or transmission purposes should not lose their required characteristics for the diagnosis after the recovery process. The recovered compressed images are evaluated by using the objective criteria of PSNR values. The experimental results are provided in the study.
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    Design of Approximate Discrete Cosine Transform Architecture for Image Compression with HEVC Intra Prediction
    (Ieee, 2020) Akman, Ali; Cekli, Serap
    Discrete cosine transform (DCT) is an integral part of many image compression standards. Image compression with HEVC inra prediction method also uses DCT. Because the complexity of DCT is high, the complexity of the encoder hardware is high and the energy consumption of the encoder is also high. In this study, a new approximated DCT architecture is proposed to reduce the complexity and energy consumption of DCT hardware used in image compression by high efficiency video coding (HEVC) intra prediction method. This architecture is based on the use of shy and add operation instead of multiplication, and the use of approximate 5:3 compressor chains for addition operations..
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    An Efficient SPIHT Algorithm and System Architecture for Image Compression
    (IEEE, 2017) Cekli, Serap; Akman, Ali
    In this study, an efficient modified SPIHT algorithm and related architecture design is proposed for image compression. The proposed architecture is designed as a three stage pipeline structure. Different sized images are compressed using the designed architecture for different bpp values. The computed PSNR values of the compressed images using the proposed algorithm and also the original algorithm is compared in order to test the performance of the proposed algorithm and architecture.
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    Enhanced SPIHT algorithm with pipelined datapath architecture design
    (İstanbul Üniversitesi Cerrahpaşa, 2019) Çekli, Serap; Akman, Ali
    Set partitioning in hierarchical trees (SPIHT) is an efficient algorithm which is used for the image compression widely. SPIHT operates sequentially so, its parallel implementation is difficult. In this study, the SPIHT algorithm is improved for providing that it is suitable for the parallel processing applications, and the corresponding pipelined datapath is designed for the proposed enhanced SPIHT algorithm. The datapath is designed to have three stages as preprocessing, list generation and output stream. In the preprocessing stage, the flags which are supports the list generation stage are constituted. List of insignificant sets (LIS), list of insignificant pixels (LIP) and list of significant pixels (LSP) are formed in list generation stage. These lists contain the bit values which generate the output bit stream. The performance of the improved datapath design has been tested by compressing different images, and the obtained results are given.
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    Görüntü sıkıştırma için verimli bir SPIHT algoritması ve sistem mimarisi
    (IEEE, 2017) Çekli, Serap; Akman, Ali
    Bu çalışmada, görüntü sıkıştırma için kullanılan SPIHT algoritmasının verimli bir uyarlaması ile ilgili mimari tasarımı önerilmiştir. Bu mimari tasarım üç aşamalı iş hattı formunda gerçekleştirilmiştir...
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    Hacimsel tıbbi görüntülerin kayıpsız sıkıştırılması için iyileştirilmiş bir yöntem
    (İzmir Katip Çelebi Üniversitesi, 2019) Akman, Ali; Çekli, Serap
    Hacimsel tıbbi görüntüler çok büyük boyutludur. Bu durum, bu tip verierin depolanması ve iletiminde sorun yaratır. Dolayısıyla, hacimsel tıbbi görüntülerin verimli teknikler kullanılarak sıkıştırılması gereklidir. Teşhis üzerinde etkili olabileceğinden tıbbi görüntülerin kayıpsız teknikler ile sıkıştırılması daha uygundur. Bu çalışmada, hacimsel tıbbi görüntülerin arasında bulunan ilintiden faydalanılarak fazlalık bilgi DPCM tekniği ile uygulanmıştır...
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    HEVC iç tahmin ile görüntü sıkıştırma için yaklaşık ayrık kosinüs dönüşümü mimarisi tasarımı
    (2020) Akman, Ali; Çekli, Serap
    Ayrık kosinüs dönüşümü (AKD) birçok görüntü sıkıştırma standardının ayrılmaz parçasıdır. HEVC’in iç tahmin yöntemi ile görüntü sıkıştırma da AKD’yi kullanır. AKD karmaşıklığı yüksek olduğundan kodlayıcı donanımının karmaşıklığı dolayısıyla enerji tüketimi de yüksektir. Bu çalışmada HEVC’in iç tahmin yöntemi ile görüntü sıkıştırmada kullanılan AKD donanımının karmaşıklığını ve enerji tüketimini azaltacak yeni bir yaklaşık AKD mimarisi önerilmiştir. Bu mimari çarpma yerine kaydır ve toplam işleminin kullanılmasına ve toplama işlemleri için yaklaşık 5:3 kompresör zincirlerinin kullanılmasına dayanmaktadır.
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    Image Compression Performance of HEVC Intra Prediction with Different Transform Coefficient Coding Methods
    (Ieee, 2018) Çekli, Serap; Akman, Ali
    HEVC is the new coding standard providing higher compression ratios with comparated to the other existent coding standards. In this study, the image compression performance using intra prediction is examined. Especially, the coding of transformation of prediction errors are handled and three different coding structure is proposed. The compression code efficiency is obtained for different block sizes and image sizes by depending on the transform coding formats. The original images are recovered by decoding codes of the compressed images, and the similarity with the original images is inspected by consideirng the PSNR values.
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    An Improved Method for Lossless Compression of Volumetric Medical Images
    (Ieee, 2019) Akman, Ali; Cekli, Serap
    Size of volumetric medical images is very large. Because of this, some problems occur while storing or transmitting this type of data. So, it is necessary to compress volumetric medical images using efficient techniques. It is more appropriate to compress medical images using lossless techniques due to it may have effects on diagnosis. In this study, a method for lossless compression of volumetric medical images was proposed. The redundancy has been reduced using DPCM technique by utilizing correlation between image slices. SAP technique has been applied to first slice. The performance is improved by applying RDPCM for each image frame after DPCM, individiually. To investigate the performance of the proposed method, some experiments have been performed using different medical images and the results are presented.
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    A management model for low powered wireless personal area networks
    (IEEE, 2018) Türk, Yekta; Akman, Ali
    Most of the researchers are investigating Internet of Things (IoT) to obtain information about our environment to control and act on it with the analysis of collected big data. An important topic with IoT is to manage the vast number of devices. In this demo, we demonstrate a management model in order to detect faults, analyze network and improve performance and connectivity in low powered mesh networks. The model can take actions when necessary and visualize those actions and the state of different managed objects. For building the proposed model, we have modified a well-known network management protocol to use for management data access and have performed fault and performance analysis in terms of values of counters collected from the interfaces. Our demonstrations indicate that the usage of the proposed method can perform well in limited bandwidth networks. At the same time, some security and device firmware related features are also added to the management system.
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    Management of Low Powered Personal Area Networks using Compression in SNMPv3
    (IEEE, 2018) Turk, Yekta; Akman, Ali
    The internet of things (IoT) is being used more and more in our lives and this area attracts interest in studying new methods. One of these methods is mesh networking technique, which is increasingly becoming more popular and is suitable for use in places where wired connectivity is unavailable. Researchers are mostly focused on developing new and efficient services for systems running on this method, but the management of devices on mesh networks remains as an important issue. The management of an increasing number of devices can become inexhaustible. IoT management is to monitor and take action on the communication from and between connected devices and also control the devices from a remote server. This is similar to traditional network management when mesh network devices are considered. There is also a critical precaution for objects which is to complete administrative operations securely. In this article we have adapted a protocol, that is mainly used in traditional network management, for using in the management low powered personal area network (LoWPAN). We made some experimental analysis and compared our approach with other well-known IoT protocols for device management perspective.
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    Tıbbi görüntülerin HEVC görüntü-içi tahmin kodlama ile sıkıştırılmasının incelenmesi
    (Biyomedikal ve Klinik Mühendisliği Derneği, 2017) Akman, Ali; Çekli, Serap
    HEVC var olan standartlara göre daha yüksek sıkıştırma başarımı sağlayan son yılların yeni kodlama standardıdır. Bu çalışma HEVC görüntü-içi tahmin yöntemi ile tıbbi görüntülerin sıkıştırılması sağlanmıştır. Depolama veya iletim gibi çeşitli amaçlar için sıkıştırılmış görüntülerin tekrar elde edilmesi sonrasında kullanımında doğru tanı için hayati öneme sahip olan özelliklerini kaybetmemesi önemlidir. Sıkıştırma işleminden sonra geri elde edilen görüntüler nesnel bir ölçüt olan PSNR değerleri bulunarak değerlendirilmiştir. Denemeler sonucu elde edilen bulgular çalışmada sunulmuştur.