ECW Compression

Producer Field Guide

HGD_Product
Producer Field Guide
HGD_Portfolio_Suite
Producer

ECW Compression

Enhanced Compression Wavelet (ECW) Imagery Format is a purpose-built, high performance imagery format created by Hexagon Geospatial. Enhanced Compressed Wavelet (ECW) format significantly reduces the size of image files with minimal deterioration in quality.

Wavelet compression involves a way of analyzing an uncompressed image in a recursive manner. This analysis results in a series of sequentially higher resolution images, each augmenting the information in the lower resolution images.

The primary steps in wavelet compression are:

  • Performing a Discrete Wavelet Transformation (DWT), quantization of the wavelet-space image sub-bands; and then
  • Encoding these sub-bands.

Wavelet images are not compressed images as such. Rather, it is the quantization and encoding stages that provide the image compression. Image decompression, or reconstruction, is achieved by completing the above steps in reverse order. Thus, to restore an original image, the compressed image is decoded, dequantized, and then an inverse DWT is performed.

Wavelet compression has not been widely used because the DWT operation consumes heavy processing power, and because most implementations perform DWT operations in memory, or by storing intermediate results on a hard disk. This limits the speed or the size of image compression. The ECW wavelet compression uses a breakthrough new technique for performing the DWT and inverse-DWT operations (see patents US6201897 and US6442298). ECW makes wavelet-based compression a practical reality.

ECW compression is more efficient when it is used to compress large image files. The minimum size image that can be compressed by ECW method is 128 x 128 pixels.

Specify Quality Level rather than Output File Size

The concept of ECW and JPEG2000 format compression is that you are compressing to a specified quality level rather than a specified file size. Choose a level of quality that benefits your needs, and use the target compression ratio to compress images within that quality range. The goal is visual similarity in quality levels between multiple files, not similar file size.

ECW Compression Ratios

When exporting to ECW images, you select a target compression ratio. This is a target only, and the actual amount of compression will vary depending on the image qualities and amount of spatial variation. Recommended values are 1 to 40 for color images and 1 to 25 for grayscale. Higher values give more file size compression, lower values give better image quality.

What is Target Compression Ratio

When compressing images there is a tradeoff between the degree of compression achieved and the quality of the resulting image when it is subsequently decoded. The highest rates of compression can only be achieved by discarding some less important data from the image, known as lossy decompression. The target compression ratio is an abstract figure representing your choice in this tradeoff. It approximates the likely ratio of input file size to output file size given certain parameters for compression.

It is important to note that the target ratio makes no guarantees about the actual output size that will be achieved, because this is dependent on the nature of the input data. Images with certain features (for example, air photos showing large regions of a similar color like oceans or forests) are easier to compress than others (completely random images). However in typical cases the actual rate of compression obtained will be greater than the target rate.

Except when compressing very small files (less than 2 MB in size), the actual compression ratio achieved is often significantly larger than the target compression ratio set by the user. The reason for this is as follows:

  • When you specify a Target Compression Ratio, the compression engine uses this value as a measure of how much information content to preserve in the image. If your image has areas that are conducive to compression (for example, desert areas or bodies of water), a greater rate of compression may be achieved while still keeping the desired information content and quality.
  • The compression engine uses multiple wavelet encoding techniques simultaneously, and adapts the best techniques depending on the area being compressed. It is important to understand that encoding techniques are applied after image quantization and do not affect the quality, even though the compression ratio may be higher than that which was requested.

At 20:1 compression, a 10GB RGB image compresses down to 500MB in size. Images with less information can achieve even greater compression ratios. For example, ratios of 100:1 or greater are not uncommon for compressed topographic maps. Because the compressed imagery is composed of multi-resolution wavelet levels, you can experience fast roaming and zooming on the imagery, even on slower media such as CD-ROM

Preserve Image Quality

When you specify a Target Compression Ratio, the compression engine uses this value as a measure of how much information content to preserve in the image. If your image has areas that are conducive to compression (for example, desert areas or bodies of water), a greater rate of compression may be achieved while still keeping the desired information content and quality.

The compression engine uses multiple wavelet encoding techniques simultaneously, and adapts the best techniques depending on the area being compressed. It is important to understand that encoding techniques are applied after image quantization and do not affect the quality, even though the compression ratio may be higher than that which was requested.

ECWP

ECWP is an acronym for Enhanced Compression Wavelet Protocol (ECWP) (see Web Services Types) used to transmit images compressed with ECW over networks such as the Internet. ECWP offers the fastest possible access to large ECW and JPEG2000 images and is fully supported by ERDAS APOLLO Essentials and Image Web Server (see patent US6633688).

Advantages of ECW Compression

Fast Direct Read viewing of imagery in various applications

  • Supported in traditional desktop GIS, CAD, and remote sensing packages.
  • Supported in Thin Web clients such as Enhanced Compression Wavelet Protocol (ECWP), Web Map Service (WMS), ImageX (See Web Services Types)
  • Supported in Mobile web browsers

Low load to distribute to very large quantity of users

  • Disseminates large quantities of imagery data to thousands of users on standard server hardware
  • Enables the largest number of users on any server hardware than any competitive product

Extremely fast compression

  • ECW technique uses a recursive algorithm pipeline technique that does not require immediate tiles to be stored to disk and then recalled during Discrete Wavelet Transformations (DWT).
  • ECW technique takes advantage of CPU L1 and L2 levels of cache to do its linear and unidirectional data flow through the DWT process.
  • Fastest imagery compression available on the market.

Results in extremely small file sizes

  • Greatly reduced disk space requirements for imagery storage. Wavelet compression technology offers very high quality results at high compression rates. For example, you can compress a color image to less than 5% of its original size (20:1 compression ratio) and compress a grayscale image to less than 10% of its original size (10:1 compression ratio). Another example, compressing 1 TB raw imagery at 1:25 target compression ratio results in less than 40 GB file size.
  • Multi-resolution wavelet levels are built into the file, resulting in no need to generate or distribute "pyramids" or "overviews", as well as fast roaming and zooming on the imagery, even on slower media such as CD-ROM. This technique is suitable for working with large imagery to be viewed at different resolutions since only the levels containing those details required for viewing are decompressed.
  • Improved disk access. The ECW format uses a technique known as clustering to locate related information in an image closely together. This reduces the number of seeks that need to be carried out - significantly improving performance when imagery is requested for a specific area.

Interoperable standards support through the Web Map Service (WMS)

  • Market proven fastest imagery Web Map Service (WMS) (see Web Services Types) available on the market today that can support large numbers of users through this traditionally high CPU intensive subsetting routine.

Streaming imagery protocol to deliver rich and continuous user experience over the internet

  • Enhanced Compression Wavelet Protocol (ECWP) (see Web Services Types) delivers massive volumes of gridded data to thousands of users on a standard server hardware set (8 or less core server hardware set).
  • Continuous imagery streaming experience produces a rich end user experience for maps with imagery.

Extremely low administration

  • Extremely low maintenance and management time for enterprise software.
  • Greatly reduce the quantity and scale of "servers" required to be managed by administrators.
  • Greatly reduce the type and quantity of physical storage required to deliver massive volumes of "pixels".