هادی هادی زاده
گروه مهندسی مخابرات، دانشگاه صنعتی قوچان
[ 1 ] - روشی نوین برای توصیف و دسته بندی تصاویر بافتی رنگی با استفاده از کُدگذاری تُنُک ویژگی‌های چهارگانی
رنگ و بافت دو مولفه بسیار مهم در تشخیص و تمایز بین اشیاء مختلف در دنیای واقعی می باشند. اخیرا، نمایش چهارگانی (کواترنیونی) تصاویر تبدیل به یک شیوه کارآمد برای توصیف تصاویر رنگی شده است. با استفاده از نمایش چهارگانی تصاویر رنگی، امکان پردازش و در نظر گرفتن اطلاعات متقابل بین کانال های رنگی تصاویر به صورت توامان فراهم می شود. تاکنون عملگرهای چهارگانی ساده ای همچون عملگرهای چرخش، انعکاس و انتقال ک...
[ 2 ] - Compressed-Sampling-Based Image Saliency Detection in the Wavelet Domain
When watching natural scenes, an overwhelming amount of information is delivered to the Human Visual System (HVS). The optic nerve is estimated to receive around 108 bits of information a second. This large amount of information can’t be processed right away through our neural system. Visual attention mechanism enables HVS to spend neural resources efficiently, only on the selected parts of the...
[ 3 ] - Block-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients
Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...
[ 4 ] - Just Noticeable Difference Estimation Using Visual Saliency in Images
Due to some physiological and physical limitations in the brain and the eye, the human visual system (HVS) is unable to perceive some changes in the visual signal whose range is lower than a certain threshold so-called just-noticeable distortion (JND) threshold. Visual attention (VA) provides a mechanism for selection of particular aspects of a visual scene so as to reduce the computational loa...
[ 5 ] - A Novel Noise-Robust Texture Classification Method Using Joint Multiscale LBP
In this paper we describe a novel noise-robust texture classification method using joint multiscale local binary pattern. The first step in texture classification is to describe the texture by extracting different features. So far, several methods have been developed for this topic, one of the most popular ones is Local Binary Pattern (LBP) method and its variants such as Completed Local Binary...