Jpeg2000: Image Quality Metrics

High-resolution digital images that are used in geo-spatial and remote sensing technologies tend to be of large sizes, especially with newer satellite imageries that provide better than 5 m spatial resolution, and thereby consuming large storage space, large transmission bandwidth, and long transmission times. Therefore, method of compressing the archived images is required before storage and transmission. JPEG2000 is the latest image compression standard offering superior compression performance. JPEG2000 compresses and decompresses the images using discrete wavelet transformation and allowing image information to be retained without much distortion or loss. Compression in JPEG2000 can be performed in both lossy and lossless fashion. Lossy compression is preferred because of its higher compression ratio. When lossy compression is performed, some amount of data is lost during the compression. Such loss of data may lead to erroneous results when analysis is performed using computer based image applications. Thus, there is a need for image quality assessment of compressed and reconstructed images using JPEG2000 at various compression ratios. This paper focuses on such studies and, using image quality metrics, experiments are conducted to compute benchmarks of compression ratios for GIS systems that can be identified for the intended use of the image without significant degradation in the results. INTRODUCTION Satellite images that are used in GIS are generally very large in size (for example the size of the multiresolution Quickbird GeoTIFF image used in this study is 380 MB), therefore compression of the images is a must before storing and transmitting to save storage space, bandwidth and to lower the transmission times. JPEG2000 is the latest image compression standard that compresses and decompresses the images using wavelet transformation opposed to its predecessor JPEG that uses Discrete Cosine Transformation. Wavelet transform-based image compression algorithms allow images to be retained without much distortion or loss when compared to JPEG, and hence are recognized as a superior method [ ]. In JPEG2000, compression can be performed in either lossy or lossless fashion. Lossless compression is favored in life critical situations where any loss in image data and quality may lead to erroneous analysis. But in various other applications lossy compression is preferred because it provides high compression ratio that result in smaller image sizes. However, the trade off is that as the compression rate increases, the spatial and spectral features of the image are lost. This paper analyses the impact of JPEG200 compression on image quality due to lossy compression. Methodology A toolkit was developed that compressed the images using the JAI and Luratech JPEG200 API. Using the toolkit, reversible compressions were performed at different rates on the test image and the JPEG2000 file was decompressed back to TIFF file format. The quality metrics were then calculated to compare the original and the reconstructed images. The test image is a 1024 x 1024 pixels subset of Quickbird multi-spectral image of Memphis, Tennessee area. The image was compressed at various compression rates and then decompressed using JPEG2000 codec and the quality metrics of the reconstructed image was computed by using the original image as a benchmark.