Earticle

본 논문은 단일 영상 기반의 초해상도에서 결과의 품질을 개선하기 위해 적응형 가중치를 적용한 잔차 블 록으로 구성된 다중 블록 구조를 이용하는 방법을 제안하였다. 딥러닝을 이용한 초해상도를 생성하는 과정에서 품질 향상을 위한 가장 중요한 요소는 특징 추출 및 적용이다. 해상도가 낮아 이미 손실된 세부사항을 복원하기 위해 다 양한 특징을 추출하는 것이 최우선이지만 네트워크의 구조가 깊어지거나 복잡해지는 등의 문제가 발생하기 때문에 실제 적용에서 제한사항이 있다. 따라서 특징 추출 과정은 효율적으로 구성하고 적용 과정을 개선하여 품질을 개선 하였다. 이를 위해 최초 특징 추출 이후 다중 블록 구조를 구성하였고 블록 내부에는 중첩된 잔차 블록을 구성한 뒤 적응형 가중치를 적용하였다. 또한 최종 고해상도 복원을 위해 다중 커널을 이용한 영상 재구성 과정을 적용함으로 써 결과물의 품질을 향상시켰다. 평가를 위해 원본 영상 대비 PSNR과 SSIM 값을 구하였고 기존 알고리즘과 비교 하여 제안하는 방법의 성능 향상을 확인하였다.

In this paper, proposes a method using a multi block structure composed of residual blocks with adaptive weights to improve the quality of results in single image super resolution. In the process of generating super resolution images using deep learning, the most critical factor for enhancing quality is feature extraction and application. While extracting various features is essential for restoring fine details that have been lost due to low resolution, issues such as increased network depth and complexity pose challenges in practical implementation. Therefore, the feature extraction process was structured efficiently, and the application process was improved to enhance quality. To achieve this, a multi block structure was designed after the initial feature extraction, with nested residual blocks inside each block, where adaptive weights were applied. Additionally, for final high resolution reconstruction, a multi kernel image reconstruction process was employed, further improving the quality of the results. The performance of the proposed method was evaluated by calculating PSNR and SSIM values compared to the original image, and its superiority was demonstrated through comparisons with existing algorithms.

컬러 영상 처리 기반의 연기 검출은 화재의 조기 검출에 적합한 검출 대상이다. 연기 검출을 위한 방법으로 움직임과 색상이 전처리로서 처리되며, 확산, 질감, 형태, 방향성 등의 성질이 후처리로서 사용된다. 본 논문은 연기의 특성 중 밀도적인 분포 특성 검출방법을 제안한다. 연기의 움직임을 10Frame 간격으로 1초 동안 축적한 이미지에 색상을 문턱치 처리해 후보영역을 생성하고,OBTP(Object Block Ternary Pattern)을 적용해 연기의 패턴임을 확인한다. 모든 처리는 Block 기반으로, 움직임 검출은 차분 영상에 적응 문턱치를 적용해 움직이는 물체의 후보영역을 결정했다. 결정된 후보영역을 1초간 축적하고 연기 색상의 문턱치 조건을적용한다. 각각의 연기 후보 영역을 특정 위치의 16개 Block 값을 중앙 Block 값과 비교하고 삼진화 된 패턴을 연기의 패턴과 비교하여 연기를 결정한다.

Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A methodfor detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke suchas diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method ofdensity distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding imagein Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whetherthe pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing isBlock-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptivethreshold to frame difference image. The decided candidate region accumulates one second and apply the threshold conditionof the smoke color. make the ternary pattern compare the center block value with block value of 16 position in eachcandidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern

디지털 워터마킹은 멀티미디어 데이터의 소유권 보호를 위해 중요한 역할을 한다. 본 논문은 DCT영역에서 효율적인 시스템적 선형 블록 코드 (SLBC)를 이용하여 디지털 이미지를 위한 새로운 워터마킹 방법을 제안한다. 제안한 SLBC 기반 워터마킹 방법은 에러 보정 능력을 제공하는 {0, 1}의 코드 시퀀스를 생성한 후 {0, 1}의 코드를 {-1, 1}의 바이너리 워터마크 시퀀스로 대치시킨다. 이러한 방법은 더욱더 강력한 보이지 않는 이미지 워터마크를 얻을 수 있으며 바이너리 시퀀스 숫자를 위한 적은 저장장소를 요구한다. 이렇게 재생된 워커마크 시퀀스는 워커마크 임베딩 프로세스와 워터마크 검출 프로세스로 구성된 제안된 워터마킹 시스템의 입력으로 사용된다. 모의 실험 결과, 제안한 방법은 가우시안 잡음, JPEG 압축, 잘라내기, 필터링 등과 같은 다양한 형태의 공격에 대해 잘 알려진 Cox 방법보다 우수한 강인성을 보여준다. 제안한 방법은 10에서 21사이의 유사성 값을 보인 반면, Cox 방법은 같은 공격에 대해 단지 7에서 19의 유사성 값을 보여준다. 이유는 이미지 처리 공격에 의해 발생된 에러가 디코더 단계에서 SLBC에 의해 보정되기 때문이고, 그 결과 강인성이 향상된다.

Digital watermarking plays an important role for copyright protection of multimedia data. This paper proposes a new watermarking method for digital images using efficient systematic linear block codes , SLBC in discrete cosine transform , DCT domain. The proposed watermarking method using SLBC generates a code sequence of {0, 1} that provides error correction capabilities and then replaces it with a binary watermark sequence of {-1, 1} which achieves more robust invisible image watermarks and requires a small storage unit for binary sequence numbers. The generated watermark sequence is then used as an input for our proposed watermarking system which consists of watermark embedding process and watermark detection process. Experimental results indicate that our proposed method outperforms the well-known Cox’s method in terms of robustness against various kinds of attacks such as white Gaussian noise, JPEG compression, cropping, and filtering. Our proposed method achieves similarity values ranging from 10 to 21. This is in contrast to the Cox’s method, which achieves similarity values ranging from only 7 to 19 for the same attacks. This is because errors generated by image processing attacks are corrected with SLBC at the decoder stage, improving the robustness.

본 논문에서는 위성영상처리 소프트웨어 및 시스템의 재사용성을 높이고, 개발기간 및 유지 관리 비용을 줄일 수 있는 알고리즘컴포넌트화를 통한 위성영상처리 프레임워크 및 시스템에 대한 구조를 제안한다. 기존 위성영상처리 소프트웨어 및 시스템은 특정데이터 및 기능에 국한되어 제한된 구조를 갖고 있다. 또한, 각각의 시스템들은 동일 및 유사한 영상처리 알고리즘이 사용되지만해당 알고리즘을 중복적으로 개발하는 문제점이 있다. 이와 같은 문제점을 해결하기 위해 위성영상처리 소프트웨어 프레임워크의요구사항을 분석하였다. 요구사항을 반영한 프레임워크 및 시스템 구조를 설계하였으며, 위성영상처리 프레임워크의 운영흐름도 함께 도출하였다.

This paper suggest meteorological satellite processing software’s structure that reduces time and efforts of modification/upgrade. This structure’s key feature is “algorithm component” that works within framework and eventually to a completeMeteorological satellite processing system. Most of existing Meteorological satellite system is designed around specificfunction and data sets which limits range of modification and upgrade. In addition, re-use of current algorithms becomedifficult although re-use of similar algorithm is the case in many occasions. This inefficiency can be resolved by designinga new framework as a result of detail analysis of collected requirements. A new framework and system architecture has beendesigned. In addition, operational flow of Satellite image processing framework has been described.

Aimed at the defects of the traditional Canny operator, this paper puts forward an improved algorithm in edge detection. First, this paper gives a new method on selfadaptive image block based on threshold value. Next, by proposing a new hybrid filterbank of self-adaptive median and morphology, we adopt this hybrid filter-bank to smooth the noise image. Then, we add the information of gradient in two bevel directions, so that the information of gradient is more complete. Last, by using the threshold value to process the image of gradient which is after non-maxima suppression, we obtain the image edge. For the noise image, this improved algorithm not only can filter out noise well, but also the image edge is continuous, smooth, clear. The experimental results show that the improved algorithm has a good effect in edge detection, strong capability of noise immunity. The objective evaluation and visual effect are good, too.

A method for image compression, adaptive difference compensation vector quantization using dynamic image block adjustment is proposed in this paper. Before image coding, this proposed method analyzes the similarity values between the encoding image sub-block and its 8-neighbor sub-blocks, then determines the encoding rule according to the similarity value and the preset threshold. If the similarity value is approximate to the threshold, we use the same codeword to encode the neighbor block and the encoding image block; otherwise, the neighbor block is separately encode. When encoding, the difference between each image block and its matching codeword is first computed to obtain the difference image, and then the sign bits of the pixel difference is imposed the running length coding on and attached after the codeword index. When decoding, this proposed method restores the compressed image according to the codeword index, performs the running length encoding to deal with decode the attached information, uses the window of 33 size to tackle the adaptive difference compensation and derive the final decoding image. The experiment results reveal that this proposed method can improve the encoding speed and image restoration performance against the normal vector quantization.

In this paper, a simple active image authentication scheme for the compressed images of block truncation coding (BTC) is proposed. In this scheme, the authentication codes of the compressed blocks are generated from the random value induced by the random seed. The authentication code of each compressed block is embedded into the bit map. The bit length of each authentication code can be chosen according to the user’s requirement. The experimental results indicate that the proposed scheme detects the tampered areas clearly and keeps good image qualities of the embedded images. Meanwhile, a low computational cost is required in the proposed scheme.

In present era all the multimedia communication is done over open network such as Images, Audio, Videos, Text etc, so the security is also a major concern. In this research we proposed an image encryption algorithm by using chaotic map as it is well known for its Dynamic nature, Randomness and very sensitive towards initial condition. In the pro-posed algorithm two dimensional chaotic map and the two secrets keys for encryption of image are used in which first we divide the image into four blocks and then each block of the image is encrypted individually in n times, after that the keys are inverted for each block and repeat this process up to m times. The proposed work has been rigorously examined over the prevalent standard test and has encouragingly succeeded to pass most of them like key sensitivity analysis, statistical analysis, differential analysis, entropy analysis, which make the proposed algorithm good enough for real time secure communication.

Transmission of block-coded images over wireless channels results in lost blocks. These losses may occur in region-of-interest (ROI) of images which contain important information of images. In this paper, we propose a new error concealment method for covering up the high packet losses of an original image after its transmission through an error-prone channel. In this scheme, Discrete Wavelet Transform (DWT) is applied to each block of the original image in order to produce a lower resolution copy of the block. Then, we choose approximation coefficients of each block as replica of the block and embed it into a remote block (called masking block) of the image in the spatial domain. We use a new algorithm to find the masking block for embedding the replica. The advantage of this algorithm is that it avoids losing simultaneously the information of the block and its masking block. It is shown that the proposed scheme provides significant improvement over existing algorithms in terms of both subjective and objective evaluations. This technique can be implemented for wireless channels to combat degradations in a backward-compatible scheme. It is also shown that this scheme can efficiently restore the lost blocks in the ROI of images.

Fragile watermarking has the characteristics where the inserted watermark should be easily breakable for a trivial tampering of the image. So, fragile watermarking technique is proposed for the purpose of authentication or tamper detection. In this paper, we propose an efficient image tamper detection method using block-wise technique which is able to detect the tamper locations. In the proposed method, a digital signature is generated from the hash code of the blocks of the final level where the watermark is inserted and the blocks of the upper level where those blocks are included in the image division process and this signature is used as the watermark, which is randomly inserted into selected image blocks. As the result of experiment, the proposed method was confirmed to be able to detect the tampered parts of the image without testing the entire block of the watermarked image.

The paper proposes an information hiding technique for steganography and digital watermarking using Bi-dimensional Empirical Mode Decomposition (BEMD) and Hilbert Transform (HT). We use RGB color image as a cover image. The cover image is divided into a number of blocks. Then each block of the cover image is putrefied into a number of Intrinsic Mode Functions (IMFs) using BEMD. We embed secret information with private key into a significant IMF. The embedded secret information, called watermark, is a matrix of 1 and -1. However, this watermark is generated by mapping pseudo-random numbers. Therefore, any unauthorized person who does not possess the private key cannot extract the watermark. The significant IMF is a highest energetic IMF which is selected according to the energy distribution of the putrefied IMFs. Thus the selected IMF is less sensitive to common image and signal processing manipulation. In watermark extraction process, we transform the watermarked object into frequency domain using HT bypassing the use of BEMD due to its empirical characteristics. Thereafter, we extract the watermark bit using block averaging technique. The experimental results of this algorithm demonstrate that the proposed method has better imperceptibility and it is more robust against several image processing and geometric manipulations.

One method to compress a pair of stereo images is to compress the first image independently and then compress the second image by estimating the disparity between the two images. The first image was transformed using 2-D Discrete Cosine Transform, quantized using the JPEG quantization matrix and finally encoded into a bitstream using arithmetic encoding. The disparity between the two images was estimated by the Exhaustive Block Matching Algorithm (EBMA) and the resulting disparity vector was then encoded into a bitstream. The images were then decoded and were compared with the original images.

In this paper, a fast and memory efficient version of set partitioned embedded block (SPECK) image coder is proposed. Due to use of linked lists, SPECK algorithm, requires large run-time memory, making it unsuitable for memory constrained portable multimedia devices and WMSN’s. The proposed coder replace linked list with fixed size static memory, to keep track of set partitions and coding information and use few markers to facilitate coding. Elimination of linked lists also reduces the memory access time and time involved in addition /deletion in memory, thereby making it faster than the original SPECK. Simulation results show that the proposed algorithm outperforms SPECK image coder in terms of memory requirement while retaining the coding efficiency and scalability property of the original SPECK. Proposed coder requires 0.75 bit per pixel state memory which is 9.38 % of the memory required to store the image. Therefore proposed NLSK coder is suitable for resource constrained portable hand held devices and WMSN’s.

A novel color image compression scheme based on block truncation coding is proposed in this paper. In this scheme, the quadtree segmentation technique is employed to partition the color image into variable-sized image blocks according to its block activities. Then, the block truncation coding scheme with the bit map omission technique is employed to encode the image blocks. According to the experimental results, the proposed scheme significantly cuts down the bit rates while keeping good reconstructed image qualities of the compressed color images.

가역 데이터 은닉 기법은 이미지에 비밀 데이터를 삽입 후, 이미지에서 삽입된 데이터를 추출한 후에 원본 이미지의 복원이 완벽하게 가능한 기법을 말하며 최근에 많은 관심을 받고 있는 분야이다. 이러한 복원 가능한 데이터 은닉 기법 중 기존의 히스토그램을 이용한 기법들은 데이터 처리를 비트 단위로 함으로서 은닉 데이터의 삽입량에 대한 효율성이 떨어지는 문제를 공유하고 있다. 본 논문에 서는 이러한 문제점을 해결하기 위해 차분 이미지 히스토그램을 이용한 이중 레벨 블록단위 가역 데 이터 은닉 기법을 제안한다. 본 논문에서 제안한 기법은 이미지 히스토그램의 역 S-순서를 블럭단위 로 적용하고 은닉 데이터 삽입량을 향상하기 위해 이중 레벨 기법을 적용한다. 실험결과 본 논문에서 제안하는 기법이 데이터 삽입량 면에서 우수한 성능을 보였다.

Reversible data hiding, which can recover the original image without any distortion after the extraction of the hidden data, has drawn considerable attention in recent years. However, the previous researches of histogram based data hiding scheme share the problem of the limit of the embedding capacity of secret data because they use bit level data processing. To overcome the problem, we propose a new twice level block-based reversible data hiding scheme using difference image histogram. The proposed scheme uses block-based inverse S-order image histogram and allows for dual-level data hiding to increase the hiding capacity. The simulation results demonstrate that the proposed scheme generates good performance in the embedding capacity.

Edge Histogram Descriptor는 image의 edge 분포 정보를 표현하며 방향성을 가지는 Bio Image 검색에 있어 높은 검색 성능을 나타낸다. 그러나 Bio Image의 객체 분포의 특성으로 인해 지역적 edge 분포 비교는 충분한 검색 성능을 보장하지는 못한다. 본 논문에서는 특징 block을 이용한 효율적인 검색 알고리즘을 제안한다. Local histogram으로부터 Global bin을 얻어 image의 대표 방향성을 선정하고 특징 block을 선정한다. 특징 block의 비교는 edge 분포와 함께 주요 객체의 위치 정보를 더하는 효과를 가진다. Bio Image의 검색 실험에서 제안 알고리즘은 향상된 검색 성능을 보여준다. 또한 Bio image 검색을 위한 descriptor 조합 연구에도 적용 가능하여 검색 효율을 기대할 수 있다.

In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

In this paper, we present a new blocking artifact reduction algorithm using interpolation and signal adaptive filter (SAF) based on the edge map. Generally, block-based coding, such as JPEG and MPEG, is the most popular image compression method. However, for high compression it produces noticeable blocking and ringing artifacts in the decoded image. In proposed method, all the block is classified into low and high frequency blocks in block classification procedure. And edge map is obtained by using Sobel operator on decoded image. And according to the block property we applied blocking artifacts reduction algorithm. Namely, four neighbor low frequency block is participated in interpolation based on edge map. And ringing artifacts is removed by applying a signal adaptive filter around the edge using edge map in high frequency block. The computer simulation results confirmed a better performance by the proposed method in both the subjective and objective image qualities.

본 논문에서는 칼라 영역으로 확장된 블록단위 영상분할 알고리듬을 제안한다. 즉, 기존의 휘도 성분을 기반으로 한 블록단위 알고리듬을 HSV 칼라 성분을 기반으로 하는 칼라 영상분할로 확장한다. 기존의 수학적 형태학(mathematical morphology)에 기반한 영상분할기법이나 블록단위 영상분할 기법들이 밝기 정보만을 활용했던 것에 대해 제안된 블록단위 영상분할 기법은 밝기뿐만이 아니라 칼라 성분도 고려하여 영상분할의 정확도를 향상시켰다. 실험의 결과 휘도 성분만을 고려한 영상분할 결과 보다 칼라 성분을 사용한 영상분할의 결과가 더 정확함을 알 수 있었다.