Global Image Compression Market Forecast to 2022

07/03/2021 by No Comments

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The image compression market is expected to grow at a CAGR of 8. 2% during the forecast period from 2016 to 2021. As the image data is increasingly being converted into the low-resolution digital format, it has become challenging for image processing applications to handle large volumes of compressed data. Hence the image compression market is experiencing significant competition from both hardware manufacturers and software vendors.

The image compression software market is expected to be dominated by the high-end compression software vendors, followed by server software vendors, and then the middle-range vendors. These three software segments are mainly driven by the need for higher compression performance, increased data throughput, and a lower overall hardware-memory overhead. Image processing technologies like the H. 264/MPEG-4 H. 264 codec, etc. adopted by both hardware and server software vendors are of major market growth. They are expected to be the fastest-growing segments in the future.

The market is also segmented on the basis of end-user applications. The server software segment has the biggest market share followed by the image processing applications segment followed by the video processing applications segment. Among them, the video processing segment is expected to witness the fastest growth followed by the server software segment.

Based on the type of image compression platform, the server software segment has the largest market share followed by the image processing applications segment. Among them, the server software segment is expected to witness major growth during the forecast period at a CAGR of 8. 2% during the forecast period. The growth of the server software market is driven by the necessity of high-end compression software for large-scale data archiving and processing. The high compression functionality, low hardware demands, and fast response time are other factors that drive the market.

Based on application type, the image processing application segment is expected to dominate the market during the forecast period at a CAGR of 6. 5% during the forecast period. The image processing application segment is driven by the need for high-performance algorithms and the fact that it requires minimal storage space.

The software market is expected to expand at a CAGR of 5.

Market Analysis of the Global Image Compression Software Market by Manufacturers, Regions, Type and Application

The global market for image compression software is expected to grow at a CAGR of 5. 10% from 2017 to 2022. Factors such as the increase of the demand for high-quality digital images have forced manufacturers to provide this software in the market. The software market for image compression is segmented on the basis of type, application and region.

264 Based Software (H.

Adobe Photoshop in the market for image compression software has played a major role in the growth of the market.

Global Image Compression Software Status and Outlook

Software Image Compression (SIC) was first defined in 1977 as a “technique to reduce the information content of a video signal by using a high quality, low data rate, signal compression technique. A high compression rate (HRC) leads to better quality and lower bit rate, while a low compression rate (LRC) leads to better quality and higher bit rate. One or more of these compression rates may be used to compress each segment of the video signal and store the compressed signal over an on-line storage medium, such as a disk or tape, to enable the video signal to be reconstructed at a later time. At the present time, different compression techniques have evolved, including H. 265, both of which provide superior compression, at a low data rate, of a video signal. The term “SIC” is often used to refer to the combination of two or more compression rates, as well as to refer to the compression and storing techniques. For example, the H. 264 compression and H. 265 compression techniques employ a combination of a H. 264 compression rate and a H. 265 compression rate. The LRC and H. 264 compression rates use the same type of data to achieve this compression.

SIC is useful in many applications. For example, in a personal computer, the data can be compressed in real-time and the compressed data can be stored on an inexpensive storage medium, such as a disk or tape. In another example, the computer can be provided with multiple input and output (I/O) devices that can communicate with the storage medium. The compression technique can be selected for the particular application. For example, the compression technique can be selected for use with a personal computer having multiple operating systems that support different video applications using different video compression standards. The SIC technique can be selected for use by the multiple video applications that simultaneously transfer video data to the storage medium.

When the data to be stored is a video signal, the data can take a variety of forms. One type of video data is a so-called “real-time” video signal. A real-time video signal can be described by a frame of video data, which contains the data of one or more frames, which can be a video sequence of one or more scenes.

The Global Image Compression Software Market Analysis with Industry Trends 2021 : Business Insights from leading players, Research with Size, Key Challenges – with Covid19.

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