Markku Vehvilainen

Bio: Markku Vehvilainen is an academic researcher from Nokia. The author has contributed to research in topics: Image restoration & Image processing. The author has an hindex of 22, co-authored 61 publications receiving 1222 citations. Previous affiliations of Markku Vehvilainen include Siemens.

Electronic device directional audio-video capture

Abstract: Disclosed herein is an apparatus. The apparatus includes a housing, electronic circuitry, and an audio-visual source tracking system. The electronic circuitry is in the housing. The audio-visual source tracking system includes a first video camera and an array of microphones. The first video camera and the array of microphones are attached to the housing. The audio-visual source tracking system is configured to receive video information from the first video camera. The audio-visual source tracking system is configured to capture audio information from the array of microphones at least partially in response to the video information. The audio-visual source tracking system might include a second video camera that is attached to the housing, wherein the first and second video cameras together estimate the beam orientation of the array of microphones.

Method, apparatus, and computer program product for providing a camera barcode reader

Abstract: An apparatus for providing a camera barcode reader includes a processing element configured to process an input image for an attempt to decode the input image using a current barcode reading method, to determine whether the processing of the input image is successful, to switch to one of a different barcode reading method or processing a new frame of the input image using the current barcode reading method in response to the processing of the input image being unsuccessful, to attempt a decode of the input image using the current barcode reading method in response to the processing of the input image being successful, and to perform a switch to the different barcode reading method in response to a failure of the attempt to decode the input image using the first barcode reading method.

Filtering based on activities inside the video blocks and at their boundary

Abstract: The invention relates to a filtering method used for a video signal at the receiver. It is mostly suited for video compression algorithms utilizing DCT-based video compression technology. In the invention the boundaries ( 49 ) between adjacent video blocks (B 5 and B 6 ) are filtered based on the amount of activity inside the adjacent video blocks and the activity at the boundary between the adjacent video blocks. If the filtering according to the invention is performed, it is focused to a certain number of bits ( 42, 43, 44, 45, 46, 47 ) close to the boundary ( 49 ). The filtering is done by adjusting the numerical values of each video pixel close to the boundary towards a reference line, which is defined as a linear equation leading from the numerical value of a first reference pixel ( 41 ) to the numerical value of a second reference pixel ( 48 ). The reference pixels ( 41, 48 ) are selected from the adjacent video blocks to present the smooth movement over the boundary between the adjacent video blocks (B 5 and B 6 ).

Constructing image panorama using frame selection

Abstract: The specification and drawings present a new method, system, apparatus and software product for constructing by an electronic device an image panorama from a plurality of images based on their visual quality. The same portion of a panoramic image scene is typically captured on multiple neighborhood video frames from which one can choose the best visual representation to be pasted into the panorama. Constructing the image panorama from the plurality of captured images can comprise the following steps: a) evaluating image quality of K consecutive frames out of the captured plurality of images using a predetermined criterion, b) selecting one image out of the evaluated K frames with the best image quality using a predetermined rule, and c) appending the selected frame to previously selected frames for constructing the image panorama. On-line and off-line implementations are possible.

Cross-color BM3D filtering of noisy raw data

Abstract: Color image reconstruction from noisy color filter array (CFA) data is considered. A modification of the Block Matching 3D (BM3D) [2] filter for CFA data denoising utilizing cross-color correlations is proposed. Denoised images are then demosaicked by algorithms developed for noise-free data leading to state-of-the-art performance for both Gaussian and Poissonian noise models.

Loss Functions for Image Restoration With Neural Networks

Abstract: Neural networks are becoming central in several areas of computer vision and image processing and different architectures have been proposed to solve specific problems. The impact of the loss layer of neural networks, however, has not received much attention in the context of image processing: the default and virtually only choice is $\ell _2$ . In this paper, we bring attention to alternative choices for image restoration. In particular, we show the importance of perceptually-motivated losses when the resulting image is to be evaluated by a human observer. We compare the performance of several losses, and propose a novel, differentiable error function. We show that the quality of the results improves significantly with better loss functions, even when the network architecture is left unchanged.

Mobile terminal and method for controlling the same

Abstract: A mobile terminal including a body; a touchscreen provided to a front and extending to side of the body and configured to display content; and a controller configured to detect one side of the body comes into contact with one side of an external terminal, display a first area on the touchscreen corresponding to a contact area of the body and the external terminal and a second area including the content, receive an input of moving the content displayed in the second area to the first area, display the content in the first area, and share the content in the first area with the external terminal.

Mobile terminal and method of controlling the same

Abstract: A mobile terminal and a method of controlling a mobile terminal may be provided. The mobile terminal may include a display to display one of a plurality of wallpapers including at least one icon; and a controller to display at least two of the plurality of wallpapers and a plurality of preview screens corresponding to the plurality of wallpapers on the display upon reception of an input of moving at least one icon, moving of the at least one icon being displayed on the displayed wallpapers and preview screens. The mobile terminal can display a movement of icon being displayed on the displayed wallpapers and preview screens. Accordingly, a user may intuitively recognize a location of icon and effectively move a location of icon.

Image Denoising Methods. A New Nonlocal Principle

Abstract: The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding performance when the image model corresponds to the algorithm assumptions but fail in general and create artifacts or remove fine structures in images. The main focus of this paper is, first, to define a general mathematical and experimental methodology to compare and classify classical image denoising algorithms and, second, to propose a nonlocal means (NL-means) algorithm addressing the preservation of structure in a digital image. The mathematical analysis is based on the analysis of the “method noise,” defined as the difference between a digital image and its denoised version. The NL-means algorithm is proven to be asymptotically optimal under a generic statistical image model. The denoising performance of all considered methods is compared in four ways; mathematical: asymptotic order of magnitude of the method noise under regularity assumptions; perceptual-mathematical: the algorithms artifacts and their explanation as a violation of the image model; quantitative experimental: by tables of $L^2$ distances of the denoised version to the original image. The fourth and perhaps most powerful evaluation method is, however, the visualization of the method noise on natural images. The more this method noise looks like a real white noise, the better the method.

Image Noise Level Estimation by Principal Component Analysis

Abstract: The problem of blind noise level estimation arises in many image processing applications, such as denoising, compression, and segmentation. In this paper, we propose a new noise level estimation method on the basis of principal component analysis of image blocks. We show that the noise variance can be estimated as the smallest eigenvalue of the image block covariance matrix. Compared with 13 existing methods, the proposed approach shows a good compromise between speed and accuracy. It is at least 15 times faster than methods with similar accuracy, and it is at least two times more accurate than other methods. Our method does not assume the existence of homogeneous areas in the input image and, hence, can successfully process images containing only textures.