scholarly journals Reduction of Artefacts in JPEG-XR Compressed Images

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1214 ◽  
Author(s):  
Kai-Lung Hua ◽  
Ho Trang ◽  
Kathiravan Srinivasan ◽  
Yung-Yao Chen ◽  
Chun-Hao Chen ◽  
...  
Keyword(s):  
Image Processing ◽  
Document Image ◽  
File Size ◽  
Quantization Parameter ◽  
High Quality ◽  
Compressed Images ◽  
Extra Step ◽  
Image Displays ◽  
Jpeg Xr

The JPEG-XR encoding process utilizes two types of transform operations: Photo Overlap Transform (POT) and Photo Core Transform (PCT). Using the Device Porting Kit (DPK) provided by Microsoft, we performed encoding and decoding processes on JPEG XR images. It was discovered that when the quantization parameter is >1-lossy compression conditions, the resulting image displays chequerboard block artefacts, border artefacts and corner artefacts. These artefacts are due to the nonlinearity of transforms used by JPEG-XR. Typically, it is not so visible; however, it can cause problems while copying and scanning applications, as it shows nonlinear transforms when the source and the target of the image have different configurations. Hence, it is important for document image processing pipelines to take such artefacts into account. Additionally, these artefacts are most problematic for high-quality settings and appear more visible at high compression ratios. In this paper, we analyse the cause of the above artefacts. It was found that the main problem lies in the step of POT and quantization. To solve this problem, the use of a “uniform matrix” is proposed. After POT (encoding) and before inverse POT (decoding), an extra step is added to multiply this uniform matrix. Results suggest that it is an easy and effective way to decrease chequerboard, border and corner artefacts, thereby improving the image quality of lossy encoding JPEG XR than the original DPK program with no increased calculation complexity or file size.

scholarly journals Enhancement of Satellite Imagesusing Image Sharpening Technique

2019 ◽  
Vol 8 (6S2) ◽  
pp. 351-354
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Histogram Equalization ◽  
Grayscale Image ◽  
Original Image ◽  
High Quality ◽  
Wide Range ◽  
Equalization Technique ◽  
The Difference

In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.

Steganographic data hiding in image processing using predictive differencing

2012 ◽  
Vol 20 (2) ◽  
Author(s):  
C. Weng ◽  
H. Tso ◽  
S. Wang
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Predictive Value ◽  
Experimental Result ◽  
Embedding Capacity ◽  
High Quality ◽  
Pixel Value ◽  
Pixel Value Differencing

AbstractIn this paper, we propose a stenography scheme based on predictive differencing to embed data in a grey-image. In order to promote the embedding capacity of pixel-value differencing (PVD), we use differencing between a predictive value and an input pixel as the predictive differencing to embed the message where a predictive value is calculated by using various predictors. If the predictive differencing is large, then it means that the input pixel is located in the edge area and, thus, has a larger embedding capacity than the pixel in a smooth area. The experimental result shows that our proposed scheme is capable of providing greater embedding capacity and high quality of stego-images then previous works. Furthermore, we have also applied various predictors to evaluate our proposed scheme.

Automated Headstone Photo Engraving

2015 ◽  
Vol 816 ◽  
pp. 313-320
Author(s):  
Daniela Perdukova ◽  
Mišel Batmend ◽  
Pavol Fedor
Keyword(s):  
Image Processing ◽  
Poor Quality ◽  
Cnc Machine ◽  
Solid Materials ◽  
High Quality ◽  
Simple Method ◽  
Cnc Machines ◽  
Data Coding ◽  
Better Than

Nowadays, machine engraving of photos into solid materials such as marble or granite is becoming very popular. Relatively cheap CNC machines are available. The problem is that high quality photos are essential to obtain good results. The first part of the paper describes a model of a CNC machine used for engraving and puts down the principles of image processing applied to poor quality photos in order to get the best results, as well as the fundamental image processing methods necessary for achieving satisfactory results when using an electromagnetic diamond percussion tool for engraving. The second part of the paper describes a very simple method of data coding and the algorithm of engraving tool movement for image engraving process by means of a control system based on ATmega16 microcontroller. The quality of the engraved images is comparable, or even better, than that of manually engraved images or images engraved by other competitive CNC machines.

scholarly journals Aplication of Image Processing to Determine The Freshness of Tilapia Fish (Oreochromis niloticus)

2019 ◽  
Vol 22 (2) ◽  
pp. 229-235
Author(s):  
Ayu Kalista ◽  
Amin Redjo ◽  
Umi Rosidah
Keyword(s):  
Image Processing ◽  
Storage Time ◽  
High Quality ◽  
Fresh Fish ◽  
A Value ◽  
Red Color ◽  
Quality Category ◽  
Independent Variable ◽  
High Quality Category

The quality of fresh fish will decrease immediately after death. One of the indicators of fish quality is the changes of the gills color. The aim of this research was to determine the changes of red color in the gills of tilapia using image processing as an indicator of fish freshness. The research method used is the Explanatory Research where the independent variable (x) is tilapia which stored at room temperature for 12 hours. The dependent variable (y) was the intensity value of red. The quality of fish could be grouped into several categories, such as high quality, good quality, limit of acceptability and spoilt. The Observation was carried out with a time of 0 hours to 12 hours (4 hour interval). The results showed that storage time affected the deterioration of fresh quality. The high quality category has a red percentage value of 82.18%. Fresh category has a red percentage value of 67.10%. The limit of acceptability category has a value of 38.52% and the spoiltcategory has a red percentage value of 9.92%.

Effects of Color Quantization on JPEG Compression

2020 ◽  
Vol 20 (03) ◽  
pp. 2050026
Author(s):  
Leonardo C. Araujo ◽  
Joao P. H. Sansao ◽  
Mario C. S. Junior
Keyword(s):  
Image Database ◽  
Quality Measures ◽  
Jpeg Compression ◽  
Natural Images ◽  
Quality Loss ◽  
Color Quantization ◽  
File Size ◽  
High Quality ◽  
Compressed Images ◽  
Small Image

This paper analyzes the effects of color quantization on standard JPEG compression. Optimized color palettes were used to quantize natural images, using dithering and chroma subsampling as optional. The resulting variations on file size and quantitative quality measures were analyzed. Preliminary results, using a small image database, show that file size suffered an average 20% increase and a concomitant loss in quality was perceived ([Formula: see text]6dB PSNR, [Formula: see text]0.16 SSIM and [Formula: see text]9.6 Butteraugli). Color quantization present itself as an ineffective tool on JPEG compression but if necessarily imposed, on high quality compressed images, it might lead to a negligible increase in data size and quality loss. In addition dithering seems to always decrease JPEG compression ratio.

A NONUNIFORM HIGH-QUALITY IMAGE COMPRESSION METHOD TO PRESERVE USER-SPECIFIED COMPRESSION RATIO

2011 ◽  
Vol 11 (03) ◽  
pp. 355-375 ◽  
Author(s):  
MOHAMMAD REZA BONYADI ◽  
MOHSEN EBRAHIMI MOGHADDAM
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Linear Mapping ◽  
Compression Method ◽  
High Quality ◽  
Compressed Images ◽  
High Quality Image ◽  
Quality Image

Most of image compression methods are based on frequency domain transforms that are followed by a quantization and rounding approach to discard some coefficients. It is obvious that the quality of compressed images highly depends on the manner of discarding these coefficients. However, finding a good balance between image quality and compression ratio is an important issue in such manners. In this paper, a new lossy compression method called linear mapping image compression (LMIC) is proposed to compress images with high quality while the user-specified compression ratio is satisfied. This method is based on discrete cosine transform (DCT) and an adaptive zonal mask. The proposed method divides image to equal size blocks and the structure of zonal mask for each block is determined independently by considering its gray-level distance (GLD). The experimental results showed that the presented method had higher pick signal to noise ratio (PSNR) in comparison with some related works in a specified compression ratio. In addition, the results were comparable with JPEG2000.

scholarly journals Recognition of Teaching Features and Behaviors in Online Open Courses Based on Image Processing

2021 ◽  
Vol 38 (1) ◽  
pp. 155-164
Author(s):  
Sheliang Li ◽  
Huaqi Chai
Keyword(s):  
Image Processing ◽  
Support Vector ◽  
Teaching Behaviors ◽  
High Quality ◽  
Behavior Recognition ◽  
Wide Audience ◽  
Teaching Behavior ◽  
And Behaviors ◽  
Open Courses

High-quality online open courses have a wide audience. To further improve the quality of these courses, it is critical to analyze the teaching behaviors in class, which are the manifestation of the overall quality of the teacher. Considering the popularity of image processing-based behavior recognition in many disciplines, this paper explores deep into the teaching features and behaviors in online open courses based on image processing. Firstly, a coding scale was designed for teaching behaviors in online open courses. Next, the principle of optical flow solving was explained for teaching video images. Then, a teaching behavior feature extraction model was established based on dual-flow deep CNN, and used to extract the key points of teacher body and the behavior features of the teacher. After that, a teaching behavior recognition method was developed combining histogram of oriented gradients (HOG) and support vector machine (SVM) to accurately allocate the teaching features and behaviors to the corresponding teaching links. Finally, the proposed model was proved effective through experiments. Based on the recognized teaching behaviors, the frequency and duration of such behaviors were subject to comparative analysis, revealing the teaching features in high-quality online open courses.

scholarly journals Quality of Experience Assessment of Video Quality in Social Clouds

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Asif Ali Laghari ◽  
Hui He ◽  
Shahid Karim ◽  
Himat Ali Shah ◽  
Nabin Kumar Karn
Keyword(s):  
Video Compression ◽  
Quality Of Experience ◽  
Service Providers ◽  
Video Quality ◽  
Original Video ◽  
File Size ◽  
High Definition ◽  
High Quality ◽  
Video Sharing

Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

scholarly journals Face Transferring on Webcam images using StyleGAN

2021 ◽  
Vol 2062 (1) ◽  
pp. 012011
Author(s):  
J. Prasanthi ◽  
G. Anuradha
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Facial Expressions ◽  
Privacy Protection ◽  
Affine Transformation ◽  
Image Transfer ◽  
Bilinear Interpolation ◽  
High Quality ◽  
The Face

Abstract In image processing technology, face transfer is broadly used for privacy protection, picture enhancement, and entertainment applications. Face transfer is the domain that maps one image into another image and extracts several features of the face from one person to morph that face to another person. This face transfer will carry the facial expressions also. This is also called face morph, face swap, etc. Here we propose StyleGAN technology using face transfer with the image to get high quality. In this StyleGAN contribute the bilinear interpolation and affine transformation. Bilinear interpolation is to remove the noise and increase the quality of images. Affine transformation is to supply the images with 2d warping to improve the image quantity. To upgrade the quality of the images with face transfer is adopted to increase the accuracy of the image quality after image transfer.

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