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Sparse representation of signals is the key for many applications, such as denoising, compression, or compressive sensing. In this paper, we propose an original adaptive wavelet filter bank that, for a class of signals, provides better compaction of information. Previously reported 1D and 2D point-wise adaptive wavelets were based on minimization of the(More)
In this paper, we present five different approaches of teaching 8-years-old children basic concepts of programming and fundamentals of computing. Using mechanical calculators, children learn some of the basic computer architecture and functionality concepts like the accumulator, counter and register shifting. The marble adding machine teaches binary number(More)
Denoising is an important issue in signal processing. Noise, caused by sensors or by quantization effects during digitalization or compression, can significantly influence the processing results. Hence, removing the noise, or extracting the signal with minimal distortion is a valuable objective for many applications. In this paper, we propose a novel robust(More)
“SUZA - from school to science and the academic community” is the official popularization program for science, technology, engineering and mathematics at University of Zagreb, Faculty of electrical engineering and computing. Volunteers in the program are professors, researchers and students from the Faculty. Although, the program is relatively(More)
In this paper, an adaptive separable 2D wavelet transform is proposed. Wavelet transforms are widely used in signal and image processing due to its energy compaction property. Sparser representation corresponds to better performance in compression, denoising, compressive sensing, sparse component analysis and many other applications. The proposed scheme(More)
We present advanced techniques for the restoration of images obtained by soft x-ray laser microscopy. We show two methods. One method is based on adaptive thresholding, while the other uses local Wiener filtering in the wavelet domain to achieve high noise gains. These wavelet based denoising techniques are improved using spatial noise modeling. The(More)
Image sharpness assessment is a very important issue in image acquisition and processing. Novel approaches in no-reference image sharpness assessment methods are based on local phase coherence (LPC), rather than edge or frequency content analysis. It has been shown that the LPC based methods are closer to human observer assessments. In this paper, we(More)
With the on-line resources becoming common one can ask what are the limitations when applied to online examinations. Standardized multiple-choice questions test are commonly used either as a tool to enable student selfexamination or as a tool to test a large number of students in a more efficient way. However, the means of delivery and what one intends the(More)
Compact representation of signals and images is a key for many applications. Compactness is often achieved through linear transforms with good energy concentration property. We present an adaptive wavelet filter bank with fixed number of vanishing moments, plus additional local adaptation. Proposed adaptation method is conducted at each sample according to(More)