Are JPEG compression and H.264 intraframe compression the same process?
This is a complex topic, so best to link and excerpt

From https://sonnati.wordpress.com/2010/10/19/h-264-for-image-compression/


  H.264 contains a number of new features that allow it to compress
  images much more efficiently than JPG.
  
  New transform design
  
  Differently from JPG, an exact-match integer 4×4 spatial block
  transform is used instead of the well known 8×8 DCT. It is
  conceptually similar to DCT but with less ringing artifacts.  There is
  also a 8×8 spatial block transform for less detailed areas and chroma.
  
  A secondary Hadamard Transform (2×2 on chroma and 4×4 on luma) can be
  usually performed on “DC” coefficients to obtain even more compression
  in smooth regions.
  
  There is also an optimized quantization and two possible zig-zag
  pattern for Run Length Encoding of transformed coefficients.
  
  Intra-frame compression
  
  H.264 introduces complex spatial prediction for intra-frame
  compression. Rather than the “DC”-only prediction found in MPEG2 and
  the transform coefficient prediction found in H.263+, H.264 defines 6
  prediction directions (modes) to predict spatial information from
  neighbouring blocks when encoded using 4×4 transform. The encoder
  tries to predict the block interpolating the color value of adiacent
  blocks. Only the delta signal is therefore transmitted.
  
  There are also 4 prediction modes for smooth color zones (16×16
  blocks). Residual data are coded with 4×4 trasforms and a further 4×4
  Hadamard trasform is used for DC coefficients.
  
  Improved quantization
  
  A new logarithmic quantization step is used (compound rate 12%). It’s
  also possible to use Frequency-customized quantization scaling
  matrices selected by the encoder for perceptual-based quantization
  optimization.
  
  Inloop deblocking filter
  
  An adaptive deblocking filter is applied to reduce eventual blocking
  artifacts at high compression ratio.
  
  Advanced Entropy Coding
  
  H.264 can use the state of the art in entropy coding: Context Adaptive
  Binary Arithmetic Coding (CABAC) which is much more efficient than the
  standard Huffman coding used in JPG.