Finally, some concluding remarks are included in Section 4. Four performance metrics were used to compare different algorithms. In Section 3, we focus on the experimental results, including the PCA only results, video approach, split band approach, and two-step approach (PCA + video codecs). Section 2 summarizes the HSI data, the technical approach, the various algorithms, and performance metrics. To the best of our knowledge, we have not seen such a study in the literature. Third, within the two-step approach, our experiments showed that the PCA + X264 combination is better than other variants in terms of performance and computational complexity. We observed that the two-step approach is better than PCA only, Video, and Split Band approaches, as perceptually lossless compression can be achieved at 100 to 1 ratio. Second, for the two-step approach, we compared four variants: PCA + J2K, PCA + X264, PCA + X265, and PCA + Daala. First, we revisited the hyperspectral image compression problem and extensively compared several approaches: PCA only, Video approach, Split Band approach, and a two-step approach. This means that perceptually lossless compression of HSI is achievable even at 100 to 1 compression. Most importantly, our investigations showed that the PCA + X264 combination can achieve more than 40 dBs of PSNR at 100 to 1 compression. In the Pavia data case, the PCA + X264 combination achieved more than 3 dBs than the PCA + J2K combination. It was observed that the combination of PCA and X264 yielded the best performance in terms of compression performance (rate-distortion curves) and computational complexity. Moreover, some alternative techniques such as video, split band, and PCA only approaches were also compared. Four video/image codecs, including J2K, X264, X265, and Daala, have been investigated and four performance metrics were used in our comparative studies. Three representative HSI data cubes such as the Pavia and AVIRIS datasets were used in our studies. The key idea is to compare several combinations of PCA and video/image codecs. Our aim is to achieve perceptually lossless compression of HSI at 100 to 1 compression. In this paper, we summarize our study in this area. In light of these new codecs, it is about time and worthwhile to revisit the HSI compression problem. #J2k band arizona free#Moreover, a free video codec known as Daala, emerged recently. X265, a fast implementation of H265, is a new codec that will succeed X264. X264, a fast implementation of H264 standard, has been widely used in Youtube and many other social media platforms. In the compression literature, there are a lot of new developments after J2K in the past 15 years. The idea was to first apply PCA to decorrelate the hundreds of bands and then a J2K codec is then applied to compress the few PCA bands. One powerful approach to HSI compression is the combination of PCA and J2K. The SB and Video approaches have been used for multispectral images and were observed to achieve reasonable performance. Another idea known as the video approach (Video) is to treat the 3-band images as video frames and compress the frames as a video. One idea known as split band (SB) is to split the hundreds of HSI bands into groups of 3-band images and then compress each 3-band image separately. There are also some conventional, simple, and somewhat naïve approaches, to compressing HSI. For instance, in, the authors have used 10 PCA compressed bands for anomaly detection. Another simple and straightforward approach is to apply PCA directly to HSI. In, a missing data approach was presented to compress HSI. In, a tensor approach was proposed to compress the HSI. In the past few decades, there are some alternative techniques for compressing HSI. In several recent papers, we have applied perceptually lossless compression to maritime images, sonar images, and Mastcam images. A simple rule of thumb is that if the peak-signal-to-noise ratio (PSNR) or human visual system (HVS) inspired metric is above 40 dBs, then the decompressed image is considered as “near perceptually lossless”. Instead, it will be more practical to apply perceptually lossless compression. Due to the presence of hundreds of bands in HSI, however, heavy burden in data storage and transmission bandwidth has been introduced.įor many practical applications, it is unnecessary to compress data losslessly because lossless compression can achieve only two to three times of compression. Hyperspectral images (HSI) have found a wide range of applications, including remote chemical monitoring, target detection, anomaly and change detection, etc.
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