specification was approved as an ISO standard for motion (video) compression in March 2010. Compression algorithm JPEG XR's design is conceptually very similar to JPEG: the source image is optionally converted to a luma-chroma colorspace, the chroma planes are optionally subsampled, each plane is divided into fixed-size blocks, the blocks are transformed into the frequency domain, and the frequency coefficients are quantized and entropy coded. Major differences include the following: JPEG supports bit depths of 8 and 12 bits; JPEG XR supports bit depths of up to 32 bits. JPEG XR also supports lossless and lossy compression of floating-point image data (by representing the floating-point values in an IEEE 754-like format, and encoding them as though they were integers) and RGBE imagery. JFIF and other typical image encoding practices specify a linear transformation from RGB to YCbCr, which is slightly lossy in practice because of roundoff error. JPEG XR specifies a lossless colorspace transformation, namely YCoCg-R, given (for RGB) by: While JPEG uses 8 × 8 blocks for its frequency transformation, JPEG XR primarily uses 4 × 4 block transforms. (2 × 4 and 2 × 2 transformations are also defined for special cases involving chroma subsampling; encoder options include YUV_444, YUV_422, YUV_420, and a monochrome Y_only.) While JPEG uses a single transformation stage, JPEG XR applies its 4 × 4 core transform in a two-level hierarchical fashion within 16 × 16 macroblock regions. This gives the transform a wavelet-like multi-resolution hierarchy and improves its compression capability. The DCT, the frequency transformation used by JPEG, is slightly lossy because of roundoff error. JPEG XR uses a type of integer transform employing a lifting scheme. The required transform, called the Photo Core Transform (PCT), resembles a 4 × 4 DCT but is lossless (exactly invertible). In fact, it is a particular realization of a larger family of binary-friendly multiplier-less transforms called the binDCT. JPEG XR allows an optional overlap prefiltering step, called the Photo Overlap Transform (POT), before each of its 4 × 4 core transform PCT stages. The filter operates on 4 × 4 blocks which are offset by 2 samples in each direction from the 4 × 4 core transform blocks. Its purpose is to improve compression capability and reduce block-boundary artifacts at low bitrates. At high bitrates, where such artifacts are typically not a problem, the prefiltering can be omitted to reduce encoding and decoding time. The overlap