Data compression with spherical wavelets and wavelets for the image-based relighting

Image compression: Maxshift ROI encoding options in JPEG2000

“…As we have previously shown, the main drawbacks of the Maxshift method are basically: (1) there is no control about the relative importance of the ROI and the BG; and (2) there is no possibility to encode different ROIs at different quality levels, according to the user priorities.…”

“…Several lossless (with exact reconstruction) and lossy (with some information loss) compression techniques have been already proposed in different research fields [1][2][3][4][5]. Current compression algorithms use Discrete Cosine Transform (DCT) or Discrete Wavelet Transform (DWT).…”

“…In this paper, we propose a new method that is valid: (1) to use the capability of selective scaling of the wavelet coefficients; (2) to have control over the relative compression of the BG and the ROI; and (3) to obtain different compression rates for different ROIs within an image. In all the cases, there is no need to code additional information about the ROI shapes, making efficient use of the standard.…”

Uniformly sampling multi-resolution analysis for image-based relighting

“…In [26], a more practical spherical Haar wavelet basis that is both orthogonal and symmetric was proposed. There are also some previous works [27,28] related to icosahedron for rendering images. However, none of these works demonstrated the advantages of using the uniformly sampling property of an icosahedron.…”

Real-time triple product relighting using spherical local-frame parameterization

“…Spherical wavelets have been used for BRDF representation [12], texture processing [13], analysis of fluid flow [10], image-based relighting [22] and other applications. Schörder et al [12] are the first to introduce the concept of spherical wavelets to graphics community.…”