Samsung Electronics Co., Ltd.

Hewlett-Packard Development Company, L.p.

Hp Printing Korea Co., Ltd.

Sergey Stanislavovich Zavalishin

Aleksei Mikhailovich Gruzdev

Xenya Yurievna Petrova

Vladimir Gennadievich Kurmanov

Dae-kyu Shin

Kwang-Hyun Lee

Hee-jun Lee

Dae-Kyu Shin

Ilya Vasilievich Kurilin

Evgeny Andreevich Dorokhov

Valery Valerievich Anisimovskiy

Gleb Andreevich Odinokikh

Alexey Bronislavovich Danilevich

Andrey Yurievich Shcherbinin

Kwang-hyun Lee

Vitaly Sergeevich Gnatyuk

Michael Nikolaevich Rychagov

Hee-Jun Lee

Gleb Sergeevich Milyukov

Artem Sergeevich Migukin

Ju-woan Yoo

Ivan Olegovich Karacharov

Vladimir Alexeevich Eremeev

Kirill Victorovich Lebedev

Alexey Mikhailovich Fartukov

Andrey Alekseevich Bout

Ivan Victorovich Glazistov

Alexander Alexandrovich Molchanov

Kirill Viktorovich Lebedev

Ilya Vasilyevich Kurilin

Dmitry Valerievich Polubotko

Maksim Alexandrovich Penkin

Ju-Woan Yoo

An image processing device includes an encoder configured to receive a blurry image and generate a global feature map of the image, a merging unit configured to merge the global feature map and blur information, a decoder configured to generate a feature tensor and weight tensors, a recurrent refinement module configured to perform recurrent feature filtering, and an image reconstruction module configured to reconstruct a deblurred image where the image processing device is configured to estimate an image global shift and to activate or deactivate the recurrent refinement module based on the estimation.

Electronic device for performing image deblurring and controlling method of electronic device

An image processing method is provided The image processing includes images obtained using a Red-Clear-Clear-Blue (RCCB) color filter array. An image processing method for processing an RCCB image obtained by an image capturing device comprising an array of photosensors with a mosaic of RCCB filters comprises interpolating the RCCB image to obtain dense C-channel data from a sparse C-channel, and chromatic filtering, based on the RCCB image data and the dense C-channel, to obtain an RGB image by obtaining the dense R-channel and B-channel, and filtering the R-channel and B-channel using the guide image. The computational load on the image processing equipment and the processing time are reduced, while enhancing the obtained image quality, including in low light conditions.

Method and apparatus for image processing

According to an aspect of an embodiment of the disclosure, an electronic device includes: a photographing device; a memory storing one or more instructions; and at least one processor configured to execute the one or more instructions stored in the memory to capture a first image by using the photographing device, perform first adjustment on an exposure value based on the first image, when the first image does not satisfy a first condition, perform second adjustment on the exposure value based on a second image acquired by applying a mask having a high weight for a region of interest to the first image, when the second image does not satisfy a second condition, adjust at least one photographing setting value based on the adjusted exposure value, and capture, by using the photographing device, a third image based on the adjusted at least one photographing setting value.

Electronic device and control method therefor

A method and an illumination manipulation device of performing an object illumination manipulation operation on a first image are provided. The method includes receiving the first image and an input of a light direction, generating a second image with a first object detected from the first image, determining a second object illumination of the second image based on the light direction and replacing a first object illumination of the first image with the second object illumination.

Method and an apparatus for performing object illumination manipulation on an image

A method and device for automatically classifying document hardcopy images by using document hardcopy image descriptors are provided. The method and device include providing a document hardcopy image, the document hardcopy image having image features, extracting image descriptors by a first set of image descriptor extractors, each image descriptor of the image descriptors being descriptive of the image features of the document hardcopy image, estimating class probabilities of the document hardcopy image by multiple trained classifiers based on the image descriptors, determining a most probable class of the document hardcopy image by a trained meta-classifier based on the class probabilities estimated by the multiple trained classifiers, inputting the document hardcopy image and the most probable class of the document hardcopy image to an assigner, and assigning, by the assigner, the most probable class determined by the trained meta-classifier to the document hardcopy image to obtain a classified document hardcopy image.

Method and device for classifying scanned documents

An approach is provided to process an image. The approach includes: obtaining a pixel shift set indicating information of movement of a plurality of pixels included in coinciding portions among a plurality of low-resolution images with respect to a single scene; dividing the pixel shift set into an integer portion and a fractional portion; generating an integer pixel shift set and a fractional pixel shift set; selecting a filter set corresponding to the plurality of pixels from among a plurality of pre-stored filter sets including a filter weight value applied to the pixels; and obtaining a high-resolution image with respect to the single scene, based on the plurality of low-resolution images, the selected filter set, and the integer pixel shift set.

Method and apparatus for processing image

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Moscow, Russia

Sergey Stanislavovich Zavalishin